Facebook

Created By

7 months ago

Overview

Tools

1 / 5

list_ad_accounts

List down the ad accounts and their names associated with your Facebook account.

CRITICAL: This function MUST automatically fetch **all** pages using pagination.
When the response contains a ``paging.next`` URL, it immediately and
automatically uses :func:`fetch_pagination_url` to retrieve the next page. This
continues until no ``next`` URL exists. It never asks the user for permission,
never stops after the first page, and always returns the complete consolidated
list of **all** ad accounts across every page in a single response.

get_details_of_ad_account

Get details of a specific ad account as per the fields provided Args: act_id: The act ID of the ad account, example: act_1234567890. If omitted, the server automatically resolves the first accessible ad account for the provided access token. fields: The fields to get from the ad account. If None, defaults are used. Available fields include: name, business_name, age, account_status, balance, amount_spent, attribution_spec, account_id, business, business_city, brand_safety_content_filter_levels, currency, created_time, id. Returns:
A dictionary containing the details of the ad account

get_adaccount_insights

Retrieves performance insights for a specified Facebook ad account.

This tool interfaces with the Facebook Graph API's Insights edge to fetch comprehensive performance data, such as impressions, reach, cost, conversions, and more. It supports various options for filtering, time breakdowns, and attribution settings. Note that some metrics returned might be estimated or in development CRITICAL: This function MUST automatically fetch **all** pages using pagination. When the response contains a ``paging.next`` URL, it immediately and automatically uses :func:`fetch_pagination_url` to retrieve the next page. This continues until no ``next`` URL exists. It never asks the user for permission, never stops after the first page, and always returns the complete consolidated list of **all** ad account insight rows across every page in a single response. This is a requirement, not optional behavior. Args: act_id (str): The target ad account ID, prefixed with 'act_', e.g., 'act_1234567890'. If omitted, the server automatically resolves the first accessible ad account for the provided access token. fields (Optional[List[str]]): A list of specific metrics and fields to retrieve. If omitted, a default set is returned by the API. Common examples include: - 'account_currency', 'account_id', 'account_name' - 'actions', 'clicks', 'conversions' - 'cpc', 'cpm', 'cpp', 'ctr' - 'frequency', 'impressions', 'reach', 'spend'. date_preset (str): A predefined relative time range for the report. Options: 'today', 'yesterday', 'this_month', 'last_month', 'this_quarter', 'maximum', 'last_3d', 'last_7d', 'last_14d', 'last_28d', 'last_30d', 'last_90d', 'last_week_mon_sun', 'last_week_sun_sat', 'last_quarter', 'last_year', 'this_week_mon_today', 'this_week_sun_today', 'this_year'. Default: 'last_30d'. This parameter is ignored if 'time_range', 'time_ranges', 'since', or 'until' is provided. time_range (Optional[Dict[str, str]]): A specific time range defined by 'since' and 'until' dates in 'YYYY-MM-DD' format, e.g., {'since': '2023-10-01', 'until': '2023-10-31'}. Overrides 'date_preset'. Ignored if 'time_ranges' is provided. time_ranges (Optional[List[Dict[str, str]]]): An array of time range objects ({'since': '...', 'until': '...'}) for comparing multiple periods. Overrides 'time_range' and 'date_preset'. Time ranges can overlap. time_increment (str | int): Specifies the granularity of the time breakdown. - An integer from 1 to 90 indicates the number of days per data point. - 'monthly': Aggregates data by month. - 'all_days': Provides a single summary row for the entire period. Default: 'all_days'. level (str): The level of aggregation for the insights. Options: 'account', 'campaign', 'adset', 'ad'. Default: 'account'. action_attribution_windows (Optional[List[str]]): Specifies the attribution windows to consider for actions (conversions). Examples: '1d_view', '7d_view', '28d_view', '1d_click', '7d_click', '28d_click', 'dda', 'default'. The API default may vary; ['7d_click', '1d_view'] is common. action_breakdowns (Optional[List[str]]): Segments the 'actions' results based on specific dimensions. Examples: 'action_device', 'action_type', 'conversion_destination', 'action_destination'. Default: ['action_type']. action_report_time (Optional[str]): Determines when actions are counted. - 'impression': Actions are attributed to the time of the ad impression. - 'conversion': Actions are attributed to the time the conversion occurred. - 'mixed': Uses 'impression' time for paid metrics, 'conversion' time for organic. Default: 'mixed'. breakdowns (Optional[List[str]]): Segments the results by dimensions like demographics or placement. Examples: 'age', 'gender', 'country', 'region', 'dma', 'impression_device', 'publisher_platform', 'platform_position', 'device_platform'. Note: Not all breakdowns can be combined. default_summary (bool): If True, includes an additional summary row in the response. Default: False. use_account_attribution_setting (bool): If True, forces the report to use the attribution settings defined at the ad account level. Default: False. use_unified_attribution_setting (bool): If True, uses the unified attribution settings defined at the ad set level. This is generally recommended for consistency with Ads Manager reporting. Default: True. filtering (Optional[List[dict]]): A list of filter objects to apply to the data. Each object should have 'field', 'operator', and 'value' keys. Example: [{'field': 'spend', 'operator': 'GREATER_THAN', 'value': 50}]. sort (Optional[str]): Specifies the field and direction for sorting the results. Format: '{field_name}_ascending' or '{field_name}_descending'. Example: 'impressions_descending'. limit (Optional[int]): The maximum number of results to return in one API response page. after (Optional[str]): A pagination cursor pointing to the next page of results. Obtained from the 'paging.cursors.after' field of a previous response. before (Optional[str]): A pagination cursor pointing to the previous page of results. Obtained from the 'paging.cursors.before' field of a previous response. offset (Optional[int]): An alternative pagination method; skips the specified number of results. Use cursor-based pagination ('after'/'before') when possible. since (Optional[str]): For time-based pagination (used if 'time_range' and 'time_ranges' are not set), the start timestamp (Unix or strtotime value). until (Optional[str]): For time-based pagination (used if 'time_range' and 'time_ranges' are not set), the end timestamp (Unix or strtotime value). locale (Optional[str]): The locale for text responses (e.g., 'en_US'). This controls language and formatting of text fields in the response. Returns: Dict: A dictionary containing the requested ad account insights. The main results are in the 'data' list, and pagination info is in the 'paging' object. Example: ```python # Get basic ad account performance for the last 30 days insights = get_adaccount_insights( act_id="act_123456789", fields=["impressions", "clicks", "spend", "ctr"], limit=25 ) # Fetch the next page if available using the pagination tool next_page_url = insights.get("paging", {}).get("next") if next_page_url: next_page_results = fetch_pagination_url(url=next_page_url) print("Fetched next page results.") ```

get_campaign_insights

Retrieves performance insights for a specific Facebook ad campaign.

Fetches statistics for a given campaign ID, allowing analysis of metrics like
impressions, clicks, conversions, spend, etc. Supports time range definitions,
breakdowns, and attribution settings.

Args:
    campaign_id (str): The ID of the target Facebook ad campaign, e.g., '23843xxxxx'.
    fields (Optional[List[str]]): A list of specific metrics and fields to retrieve.
        Common examples: 'campaign_name', 'account_id', 'impressions', 'clicks',
        'spend', 'ctr', 'reach', 'actions', 'objective', 'cost_per_action_type',
        'conversions', 'cpc', 'cpm', 'cpp', 'frequency', 'date_start', 'date_stop'.
    date_preset (str): A predefined relative time range for the report.
        Options: 'today', 'yesterday', 'this_month', 'last_month', 'this_quarter',
        'maximum', 'last_3d', 'last_7d', 'last_14d', 'last_28d', 'last_30d',
        'last_90d', 'last_week_mon_sun', 'last_week_sun_sat', 'last_quarter',
        'last_year', 'this_week_mon_today', 'this_week_sun_today', 'this_year'.
        Default: 'last_30d'. Ignored if 'time_range', 'time_ranges', 'since', or 'until' is used.
    time_range (Optional[Dict[str, str]]): A specific time range {'since':'YYYY-MM-DD','until':'YYYY-MM-DD'}.
        Overrides 'date_preset'. Ignored if 'time_ranges' is provided.
    time_ranges (Optional[List[Dict[str, str]]]): An array of time range objects for comparison.
        Overrides 'time_range' and 'date_preset'.
    time_increment (str | int): Specifies the granularity of the time breakdown.
        - Integer (1-90): number of days per data point.
        - 'monthly': Aggregates data by month.
        - 'all_days': Single summary row for the period.
        Default: 'all_days'.
    action_attribution_windows (Optional[List[str]]): Specifies attribution windows for actions.
        Examples: '1d_view', '7d_click', '28d_click', etc. Default depends on API/settings.
    action_breakdowns (Optional[List[str]]): Segments 'actions' results. Examples: 'action_device', 'action_type'.
        Default: ['action_type'].
    action_report_time (Optional[str]): Determines when actions are counted ('impression', 'conversion', 'mixed').
        Default: 'mixed'.
    breakdowns (Optional[List[str]]): Segments results by dimensions. Examples: 'age', 'gender', 'country',
        'publisher_platform', 'impression_device'.
    default_summary (bool): If True, includes an additional summary row. Default: False.
    use_account_attribution_setting (bool): If True, uses the ad account's attribution settings. Default: False.
    use_unified_attribution_setting (bool): If True, uses unified attribution settings. Default: True.
    level (Optional[str]): Level of aggregation ('campaign', 'adset', 'ad'). Default: 'campaign'.
    filtering (Optional[List[dict]]): List of filter objects {'field': '...', 'operator': '...', 'value': '...'}.
    sort (Optional[str]): Field and direction for sorting ('{field}_ascending'/'_descending').
    limit (Optional[int]): Maximum number of results per page.
    after (Optional[str]): Pagination cursor for the next page.
    before (Optional[str]): Pagination cursor for the previous page.
    offset (Optional[int]): Alternative pagination: skips N results.
    since (Optional[str]): Start timestamp for time-based pagination (if time ranges absent).
    until (Optional[str]): End timestamp for time-based pagination (if time ranges absent).
    locale (Optional[str]): The locale for text responses (e.g., 'en_US'). This controls 
        language and formatting of text fields in the response.

Returns:
    Dict: A dictionary containing the requested campaign insights, with 'data' and 'paging' keys.

Example:
    ```python
    # Get basic campaign performance for the last 7 days
    insights = get_campaign_insights(
        campaign_id="23843xxxxx",
        fields=["campaign_name", "impressions", "clicks", "spend"],
        date_preset="last_7d",
        limit=50
    )

    # Fetch the next page if available
    next_page_url = insights.get("paging", {}).get("next")
    if next_page_url:
        next_page_results = fetch_pagination_url(url=next_page_url)
    ```

get_adset_insights

Retrieves performance insights for a specific Facebook ad set.

Provides advertising performance statistics for an ad set, allowing for analysis
of metrics across its child ads. Supports time range definitions, breakdowns,
filtering, sorting, and attribution settings. Some metrics may be estimated
or in development.

Args:
    adset_id (str): The ID of the target ad set, e.g., '6123456789012'.
    fields (Optional[List[str]]): A list of specific metrics and fields. Common examples:
        'adset_name', 'campaign_name', 'account_id', 'impressions', 'clicks', 'spend',
        'ctr', 'reach', 'frequency', 'actions', 'conversions', 'cpc', 'cpm', 'cpp',
        'cost_per_action_type', 'video_p25_watched_actions', 'website_purchases'.
    date_preset (str): A predefined relative time range ('last_30d', 'last_7d', etc.).
        Default: 'last_30d'. Ignored if 'time_range', 'time_ranges', 'since', or 'until' is used.
    time_range (Optional[Dict[str, str]]): Specific time range {'since':'YYYY-MM-DD','until':'YYYY-MM-DD'}.
        Overrides 'date_preset'. Ignored if 'time_ranges' is provided.
    time_ranges (Optional[List[Dict[str, str]]]): Array of time range objects for comparison.
        Overrides 'time_range' and 'date_preset'.
    time_increment (str | int): Granularity of the time breakdown ('all_days', 'monthly', 1-90 days).
        Default: 'all_days'.
    action_attribution_windows (Optional[List[str]]): Specifies attribution windows for actions.
        Examples: '1d_view', '7d_click'. Default depends on API/settings.
    action_breakdowns (Optional[List[str]]): Segments 'actions' results. Examples: 'action_device', 'action_type'.
        Default: ['action_type'].
    action_report_time (Optional[str]): Time basis for action stats ('impression', 'conversion', 'mixed').
        Default: 'mixed'.
    breakdowns (Optional[List[str]]): Segments results by dimensions. Examples: 'age', 'gender', 'country',
        'publisher_platform', 'impression_device', 'platform_position'.
    default_summary (bool): If True, includes an additional summary row. Default: False.
    use_account_attribution_setting (bool): If True, uses the ad account's attribution settings. Default: False.
    use_unified_attribution_setting (bool): If True, uses unified attribution settings. Default: True.
    level (Optional[str]): Level of aggregation ('adset', 'ad'). Default: 'adset'.
    filtering (Optional[List[dict]]): List of filter objects {'field': '...', 'operator': '...', 'value': '...'}.
    sort (Optional[str]): Field and direction for sorting ('{field}_ascending'/'_descending').
    limit (Optional[int]): Maximum number of results per page.
    after (Optional[str]): Pagination cursor for the next page.
    before (Optional[str]): Pagination cursor for the previous page.
    offset (Optional[int]): Alternative pagination: skips N results.
    since (Optional[str]): Start timestamp for time-based pagination (if time ranges absent).
    until (Optional[str]): End timestamp for time-based pagination (if time ranges absent).
    locale (Optional[str]): The locale for text responses (e.g., 'en_US'). This controls 
        language and formatting of text fields in the response.

Returns:    
    Dict: A dictionary containing the requested ad set insights, with 'data' and 'paging' keys.

Example:
    ```python
    # Get ad set performance with breakdown by device for last 14 days
    insights = get_adset_insights(
        adset_id="6123456789012",
        fields=["adset_name", "impressions", "spend"],
        breakdowns=["impression_device"],
        date_preset="last_14d"
    )

    # Fetch the next page if available
    next_page_url = insights.get("paging", {}).get("next")
    if next_page_url:
        next_page_results = fetch_pagination_url(url=next_page_url)
    ```

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Find what you need faster across complex wikis.","createdAt":"$D2025-10-09T03:58:11.668Z","homepage":null,"verified":true,"useCount":649,"isDeployed":true,"remote":true,"iconUrl":"https://spjawbfpwezjfmicopsl.supabase.co/storage/v1/object/public/server-icons/fd13505d-9ced-4de3-92c6-e1fbeddbf85f.webp"}}]]}]]}]\n"]) pages using pagination.\n When the response contains a paging.next URL, it immediately and\n automatically uses :func:fetch_pagination_url to retrieve the next page. This\n continues until no next URL exists. It never asks the user for permission,\n never stops after the first page, and always returns the complete consolidated\n list of all ad account insight rows across every page in a single\n response. This is a requirement, not optional behavior.\n\n Args:\n act_id (str): The target ad account ID, prefixed with 'act', e.g., 'act_1234567890'.\n If omitted, the server automatically resolves the first accessible ad\n account for the provided access token.\n fields (Optional[List[str]]): A list of specific metrics and fields to retrieve.\n If omitted, a default set is returned by the API. Common examples include:\n - 'account_currency', 'account_id', 'account_name'\n - 'actions', 'clicks', 'conversions'\n - 'cpc', 'cpm', 'cpp', 'ctr'\n - 'frequency', 'impressions', 'reach', 'spend'.\n date_preset (str): A predefined relative time range for the report.\n Options: 'today', 'yesterday', 'this_month', 'last_month', 'this_quarter',\n 'maximum', 'last_3d', 'last_7d', 'last_14d', 'last_28d', 'last_30d',\n 'last_90d', 'last_week_mon_sun', 'last_week_sun_sat', 'last_quarter',\n 'last_year', 'this_week_mon_today', 'this_week_sun_today', 'this_year'.\n Default: 'last_30d'. This parameter is ignored if 'time_range', 'time_ranges',\n 'since', or 'until' is provided.\n time_range (Optional[Dict[str, str]]): A specific time range defined by 'since' and 'until'\n dates in 'YYYY-MM-DD' format, e.g., {'since': '2023-10-01', 'until': '2023-10-31'}.\n Overrides 'date_preset'. Ignored if 'time_ranges' is provided.\n time_ranges (Optional[List[Dict[str, str]]]): An array of time range objects\n ({'since': '...', 'until': '...'}) for comparing multiple periods. Overrides\n 'time_range' and 'date_preset'. Time ranges can overlap.\n time_increment (str | int): Specifies the granularity of the time breakdown.\n - An integer from 1 to 90 indicates the number of days per data point.\n - 'monthly': Aggregates data by month.\n - 'all_days': Provides a single summary row for the entire period.\n Default: 'all_days'.\n level (str): The level of aggregation for the insights.\n Options: 'account', 'campaign', 'adset', 'ad'.\n Default: 'account'.\n action_attribution_windows (Optional[List[str]]): Specifies the attribution windows\n to consider for actions (conversions). Examples: '1d_view', '7d_view',\n '28d_view', '1d_click', '7d_click', '28d_click', 'dda', 'default'.\n The API default may vary; ['7d_click', '1d_view'] is common.\n action_breakdowns (Optional[List[str]]): Segments the 'actions' results based on\n specific dimensions. Examples: 'action_device', 'action_type',\n 'conversion_destination', 'action_destination'. Default: ['action_type'].\n action_report_time (Optional[str]): Determines when actions are counted.\n - 'impression': Actions are attributed to the time of the ad impression.\n - 'conversion': Actions are attributed to the time the conversion occurred.\n - 'mixed': Uses 'impression' time for paid metrics, 'conversion' time for organic.\n Default: 'mixed'.\n breakdowns (Optional[List[str]]): Segments the results by dimensions like demographics\n or placement. Examples: 'age', 'gender', 'country', 'region', 'dma',\n 'impression_device', 'publisher_platform', 'platform_position', 'device_platform'.\n Note: Not all breakdowns can be combined.\n default_summary (bool): If True, includes an additional summary row in the response.\n Default: False.\n use_account_attribution_setting (bool): If True, forces the report to use the\n attribution settings defined at the ad account level. Default: False.\n use_unified_attribution_setting (bool): If True, uses the unified attribution\n settings defined at the ad set level. This is generally recommended for\n consistency with Ads Manager reporting. Default: True.\n filtering (Optional[List[dict]]): A list of filter objects to apply to the data.\n Each object should have 'field', 'operator', and 'value' keys.\n Example: [{'field': 'spend', 'operator': 'GREATER_THAN', 'value': 50}].\n sort (Optional[str]): Specifies the field and direction for sorting the results.\n Format: '{field_name}_ascending' or '{field_name}_descending'.\n Example: 'impressions_descending'.\n limit (Optional[int]): The maximum number of results to return in one API response page.\n after (Optional[str]): A pagination cursor pointing to the next page of results.\n Obtained from the 'paging.cursors.after' field of a previous response.\n before (Optional[str]): A pagination cursor pointing to the previous page of results.\n Obtained from the 'paging.cursors.before' field of a previous response.\n offset (Optional[int]): An alternative pagination method; skips the specified\n number of results. Use cursor-based pagination ('after'/'before') when possible.\n since (Optional[str]): For time-based pagination (used if 'time_range' and 'time_ranges'\n are not set), the start timestamp (Unix or strtotime value).\n until (Optional[str]): For time-based pagination (used if 'time_range' and 'time_ranges'\n are not set), the end timestamp (Unix or strtotime value).\n locale (Optional[str]): The locale for text responses (e.g., 'en_US'). This controls \n language and formatting of text fields in the response.\n\n Returns:\n Dict: A dictionary containing the requested ad account insights. The main results\n are in the 'data' list, and pagination info is in the 'paging' object.\n\n Example:\n

python\n        # Get basic ad account performance for the last 30 days\n        insights = get_adaccount_insights(\n            act_id=\"act_123456789\",\n            fields=[\"impressions\", \"clicks\", \"spend\", \"ctr\"],\n            limit=25\n        )\n\n        # Fetch the next page if available using the pagination tool\n        next_page_url = insights.get(\"paging\", {}).get(\"next\")\n        if next_page_url:\n            next_page_results = fetch_pagination_url(url=next_page_url)\n            print(\"Fetched next page results.\")\n

\n "])\n "])\n "])\n "])\n "])\n "])\n "])',\n e.g., 'act_1234567890'. If omitted, the server automatically\n resolves the first accessible ad account for the provided\n access token.\n fields (Optional[List[str]]): A list of specific fields to retrieve for each ad. \n If None, a default set of fields will be returned.\n Common fields include:\n - 'id': The ad's ID\n - 'name': The ad's name\n - 'adset_id': The ID of the ad set this ad belongs to\n - 'campaign_id': The ID of the campaign this ad belongs to\n - 'creative': The ad creative details\n - 'status': The current status of the ad\n - 'effective_status': The effective status including review status\n - 'bid_amount': The bid amount for this ad\n - 'configured_status': The configured status\n - 'created_time': When the ad was created\n - 'updated_time': When the ad was last updated\n - 'targeting': Targeting criteria\n - 'conversion_specs': Conversion specs\n - 'recommendations': Recommendations for improving the ad\n - 'preview_shareable_link': Link for previewing the ad\n filtering (Optional[List[dict]]): A list of filter objects to apply to the data.\n Each object should have 'field', 'operator', and 'value' keys.\n limit (Optional[int]): Maximum number of ads to return per page. Default is 25.\n after (Optional[str]): Pagination cursor for the next page. From response['paging']['cursors']['after'].\n before (Optional[str]): Pagination cursor for the previous page. From response['paging']['cursors']['before'].\n date_preset (Optional[str]): A predefined relative date range for selecting ads.\n Options include 'today', 'yesterday', 'this_week', etc.\n time_range (Optional[Dict[str, str]]): A custom time range with 'since' and 'until' \n dates in 'YYYY-MM-DD' format.\n updated_since (Optional[int]): Return ads that have been updated since this Unix timestamp.\n effective_status (Optional[List[str]]): Filter ads by their effective status. \n Options include: 'ACTIVE', 'PAUSED', 'DELETED', \n 'PENDING_REVIEW', 'DISAPPROVED', 'PREAPPROVED', \n 'PENDING_BILLING_INFO', 'CAMPAIGN_PAUSED', 'ARCHIVED', \n 'ADSET_PAUSED', 'IN_PROCESS', 'WITH_ISSUES'.\n \n Returns:\n Dict: A dictionary containing the requested ads. The main results are in the 'data'\n list, and pagination info is in the 'paging' object.\n \n Example:\n

python\n        # Get active ads from an ad account\n        ads = get_ads_by_adaccount(\n            act_id=\"act_123456789\",\n            fields=[\"name\", \"adset_id\", \"campaign_id\", \"effective_status\", \"created_time\"],\n            effective_status=[\"ACTIVE\"],\n            limit=50\n        )\n        \n        # Fetch the next page if available using the pagination cursor\n        next_page_cursor = ads.get(\"paging\", {}).get(\"cursors\", {}).get(\"after\")\n        if next_page_cursor:\n            next_page = get_ads_by_adaccount(\n                act_id=\"act_123456789\",\n                fields=[\"name\", \"adset_id\", \"campaign_id\", \"effective_status\", \"created_time\"],\n                effective_status=[\"ACTIVE\"],\n                limit=50,\n                after=next_page_cursor\n            )\n

\n "])\n "])\n "])\n "])\n "])',\n e.g., 'act_1234567890'. If omitted, the server automatically\n resolves the first accessible ad account for the provided\n access token.\n fields (Optional[List[str]]): A list of specific fields to retrieve for each ad set. \n If None, a default set of fields will be returned.\n See get_adset_by_id for a comprehensive list of available fields.\n filtering (Optional[List[dict]]): A list of filter objects to apply to the data.\n Each object should have 'field', 'operator', and 'value' keys.\n Operators include: 'EQUAL', 'NOT_EQUAL', 'GREATER_THAN',\n 'GREATER_THAN_OR_EQUAL', 'LESS_THAN', 'LESS_THAN_OR_EQUAL',\n 'IN_RANGE', 'NOT_IN_RANGE', 'CONTAIN', 'NOT_CONTAIN',\n 'IN', 'NOT_IN', 'EMPTY', 'NOT_EMPTY'.\n Example: [{'field': 'daily_budget', 'operator': 'GREATER_THAN', 'value': 1000}]\n limit (Optional[int]): Maximum number of ad sets to return per page. Default is 25, max is 100.\n after (Optional[str]): Pagination cursor for the next page. From response['paging']['cursors']['after'].\n before (Optional[str]): Pagination cursor for the previous page. From response['paging']['cursors']['before'].\n date_preset (Optional[str]): A predefined relative date range for selecting ad sets.\n Options include: 'today', 'yesterday', 'this_month', 'last_month', \n 'this_quarter', 'lifetime', 'last_3d', 'last_7d', 'last_14d', \n 'last_28d', 'last_30d', 'last_90d', 'last_quarter', 'last_year', \n 'this_week_mon_today', 'this_week_sun_today', 'this_year'.\n time_range (Optional[Dict[str, str]]): A custom time range with 'since' and 'until' \n dates in 'YYYY-MM-DD' format.\n Example: {'since': '2023-01-01', 'until': '2023-01-31'}\n updated_since (Optional[int]): Return ad sets that have been updated since this Unix timestamp.\n effective_status (Optional[List[str]]): Filter ad sets by their effective status. \n Options include: 'ACTIVE', 'PAUSED', 'DELETED', \n 'PENDING_REVIEW', 'DISAPPROVED', 'PREAPPROVED', \n 'PENDING_BILLING_INFO', 'CAMPAIGN_PAUSED', 'ARCHIVED', \n 'WITH_ISSUES'.\n date_format (Optional[str]): Format for date responses. Options:\n - 'U': Unix timestamp (seconds since epoch)\n - 'Y-m-d H:i:s': MySQL datetime format\n - None: ISO 8601 format (default)\n \n Returns:\n Dict: A dictionary containing the requested ad sets. The main results are in the 'data'\n list, and pagination info is in the 'paging' object.\n \n Example:\n

python\n        # Get active ad sets from an ad account\n        adsets = get_adsets_by_adaccount(\n            act_id=\"act_123456789\",\n            fields=[\"name\", \"campaign_id\", \"effective_status\", \"daily_budget\", \"targeting\"],\n            effective_status=[\"ACTIVE\"],\n            limit=50\n        )\n        \n        # Get ad sets with daily budget above a certain amount\n        high_budget_adsets = get_adsets_by_adaccount(\n            act_id=\"act_123456789\",\n            fields=[\"name\", \"daily_budget\", \"lifetime_budget\"],\n            filtering=[{'field': 'daily_budget', 'operator': 'GREATER_THAN', 'value': 5000}],\n            limit=100\n        )\n        \n        # Fetch the next page if available using the pagination cursor\n        next_page_cursor = adsets.get(\"paging\", {}).get(\"cursors\", {}).get(\"after\")\n        if next_page_cursor:\n            next_page = get_adsets_by_adaccount(\n                act_id=\"act_123456789\",\n                fields=[\"name\", \"campaign_id\", \"effective_status\", \"daily_budget\"],\n                effective_status=[\"ACTIVE\"],\n                limit=50,\n                after=next_page_cursor\n            )\n

\n "])\n "])\n "])',\n e.g., 'act_1234567890'. If omitted, the server automatically\n resolves the first accessible ad account for the provided\n access token.\n fields (Optional[List[str]]): A list of specific fields to retrieve for each campaign.\n If None, a default set of fields will be returned.\n See get_campaign_by_id for a comprehensive list of available fields.\n filtering (Optional[List[dict]]): A list of filter objects to apply to the data.\n Each object should have 'field', 'operator', and 'value' keys.\n Operators include: 'EQUAL', 'NOT_EQUAL', 'GREATER_THAN',\n 'GREATER_THAN_OR_EQUAL', 'LESS_THAN', 'LESS_THAN_OR_EQUAL',\n 'IN_RANGE', 'NOT_IN_RANGE', 'CONTAIN', 'NOT_CONTAIN',\n 'IN', 'NOT_IN', 'EMPTY', 'NOT_EMPTY'.\n Example: [{'field': 'daily_budget', 'operator': 'GREATER_THAN', 'value': 1000}]\n limit (Optional[int]): Maximum number of campaigns to return per page. Default is 25, max is 100.\n after (Optional[str]): Pagination cursor for the next page. From response['paging']['cursors']['after'].\n before (Optional[str]): Pagination cursor for the previous page. From response['paging']['cursors']['before'].\n date_preset (Optional[str]): A predefined relative date range for selecting campaigns.\n Options include: 'today', 'yesterday', 'this_month', 'last_month', \n 'this_quarter', 'maximum', 'last_3d', 'last_7d', 'last_14d', \n 'last_28d', 'last_30d', 'last_90d', 'last_week_mon_sun', \n 'last_week_sun_sat', 'last_quarter', 'last_year', \n 'this_week_mon_today', 'this_week_sun_today', 'this_year'.\n time_range (Optional[Dict[str, str]]): A custom time range with 'since' and 'until' \n dates in 'YYYY-MM-DD' format.\n Example: {'since': '2023-01-01', 'until': '2023-01-31'}\n updated_since (Optional[int]): Return campaigns that have been updated since this Unix timestamp.\n effective_status (Optional[List[str]]): Filter campaigns by their effective status. \n Options include: 'ACTIVE', 'PAUSED', 'DELETED', \n 'PENDING_REVIEW', 'DISAPPROVED', 'PREAPPROVED', \n 'PENDING_BILLING_INFO', 'ARCHIVED', 'WITH_ISSUES'.\n is_completed (Optional[bool]): If True, returns only completed campaigns. If False, returns \n only active campaigns. If None, returns both.\n special_ad_categories (Optional[List[str]]): Filter campaigns by special ad categories.\n Options include: 'EMPLOYMENT', 'HOUSING', 'CREDIT', \n 'ISSUES_ELECTIONS_POLITICS', 'NONE'.\n objective (Optional[List[str]]): Filter campaigns by advertising objective.\n Options include: 'APP_INSTALLS', 'BRAND_AWARENESS', \n 'CONVERSIONS', 'EVENT_RESPONSES', 'LEAD_GENERATION', \n 'LINK_CLICKS', 'LOCAL_AWARENESS', 'MESSAGES', 'OFFER_CLAIMS', \n 'PAGE_LIKES', 'POST_ENGAGEMENT', 'PRODUCT_CATALOG_SALES', \n 'REACH', 'STORE_VISITS', 'VIDEO_VIEWS'.\n buyer_guarantee_agreement_status (Optional[List[str]]): Filter campaigns by buyer guarantee agreement status.\n Options include: 'APPROVED', 'NOT_APPROVED'.\n date_format (Optional[str]): Format for date responses. Options:\n - 'U': Unix timestamp (seconds since epoch)\n - 'Y-m-d H:i:s': MySQL datetime format\n - None: ISO 8601 format (default)\n include_drafts (Optional[bool]): If True, includes draft campaigns in the results.\n \n Returns:\n Dict: A dictionary containing the requested campaigns. The main results are in the 'data'\n list, and pagination info is in the 'paging' object.\n \n Example:\n

python\n        # Get active campaigns from an ad account\n        campaigns = get_campaigns_by_adaccount(\n            act_id=\"act_123456789\",\n            fields=[\"name\", \"objective\", \"effective_status\", \"created_time\"],\n            effective_status=[\"ACTIVE\"],\n            limit=50\n        )\n        \n        # Get campaigns with specific objectives\n        lead_gen_campaigns = get_campaigns_by_adaccount(\n            act_id=\"act_123456789\",\n            fields=[\"name\", \"objective\", \"spend_cap\", \"daily_budget\"],\n            objective=[\"LEAD_GENERATION\", \"CONVERSIONS\"],\n            date_format=\"U\"\n        )\n        \n        # Get campaigns created in a specific date range\n        date_filtered_campaigns = get_campaigns_by_adaccount(\n            act_id=\"act_123456789\",\n            fields=[\"name\", \"created_time\", \"objective\"],\n            time_range={\"since\": \"2023-01-01\", \"until\": \"2023-01-31\"}\n        )\n        \n        # Fetch the next page if available using the pagination cursor\n        next_page_cursor = campaigns.get(\"paging\", {}).get(\"cursors\", {}).get(\"after\")\n        if next_page_cursor:\n            next_page = get_campaigns_by_adaccount(\n                act_id=\"act_123456789\",\n                fields=[\"name\", \"objective\", \"effective_status\", \"created_time\"],\n                effective_status=[\"ACTIVE\"],\n                limit=50,\n                after=next_page_cursor\n            )\n

\n "])', e.g., 'act_1234567890'.\n If omitted, the server automatically resolves the first accessible ad\n account for the provided access token.\n fields (Optional[List[str]]): A list of specific fields to retrieve. If None,\n all available fields will be returned. Available fields include:\n - 'actor_id': ID of the user who made the change\n - 'actor_name': Name of the user who made the change\n - 'application_id': ID of the application used to make the change\n - 'application_name': Name of the application used to make the change\n - 'changed_data': Details about what was changed in JSON format\n - 'date_time_in_timezone': The timestamp in the account's timezone\n - 'event_time': The timestamp of when the event occurred\n - 'event_type': The specific type of change that was made (numeric code)\n - 'extra_data': Additional data related to the change in JSON format\n - 'object_id': ID of the object that was changed (ad, campaign, etc.)\n - 'object_name': Name of the object that was changed\n - 'object_type': Type of object being modified, values include:\n 'AD', 'ADSET', 'CAMPAIGN', 'ACCOUNT', 'IMAGE', 'REPORT', etc.\n - 'translated_event_type': Human-readable description of the change made,\n examples include: 'ad created', 'campaign budget updated', \n 'targeting updated', 'ad status changed', etc.\n limit (Optional[int]): Maximum number of activities to return per page.\n Default behavior returns a server-determined number of results.\n after (Optional[str]): Pagination cursor for the next page of results.\n Obtained from the 'paging.cursors.after' field in the previous response.\n before (Optional[str]): Pagination cursor for the previous page of results.\n Obtained from the 'paging.cursors.before' field in the previous response.\n time_range (Optional[Dict[str, str]]): A custom time range with 'since' and 'until'\n dates in 'YYYY-MM-DD' format. Example: {'since': '2023-01-01', 'until': '2023-01-31'}\n This parameter overrides the since/until parameters if both are provided.\n since (Optional[str]): Start date in YYYY-MM-DD format. Defines the beginning \n of the time range for returned activities. Ignored if 'time_range' is provided.\n until (Optional[str]): End date in YYYY-MM-DD format. Defines the end \n of the time range for returned activities. Ignored if 'time_range' is provided.\n \n Returns:\n Dict: A dictionary containing the requested activities. The main results are in the 'data'\n list, and pagination info is in the 'paging' object. Each activity object contains\n information about who made the change, what was changed, when it occurred, and\n the specific details of the change.\n \n Example:\n

python\n        # Get recent activities for an ad account with default one week of data\n        activities = get_activities_by_adaccount(\n            act_id=\"act_123456789\",\n            fields=[\"event_time\", \"actor_name\", \"object_type\", \"translated_event_type\"]\n        )\n        \n        # Get all activities from a specific date range\n        dated_activities = get_activities_by_adaccount(\n            act_id=\"act_123456789\",\n            time_range={\"since\": \"2023-01-01\", \"until\": \"2023-01-31\"},\n            fields=[\"event_time\", \"actor_name\", \"object_type\", \"translated_event_type\", \"extra_data\"]\n        )\n        \n        # Paginate through activity results\n        paginated_activities = get_activities_by_adaccount(\n            act_id=\"act_123456789\",\n            limit=50,\n            fields=[\"event_time\", \"actor_name\", \"object_type\", \"translated_event_type\"]\n        )\n        \n        # Get the next page using the cursor from the previous response\n        next_page_cursor = paginated_activities.get(\"paging\", {}).get(\"cursors\", {}).get(\"after\")\n        if next_page_cursor:\n            next_page = get_activities_by_adaccount(\n                act_id=\"act_123456789\",\n                fields=[\"event_time\", \"actor_name\", \"object_type\", \"translated_event_type\"],\n                after=next_page_cursor\n            )\n

\n "])\n "]) Session Configuration","$schema":"https://json-schema.org/draft/2020-12/schema","required":["fbToken"],"properties":{"fbToken":{"type":"string","description":"Facebook Access Token to be used with the server."}},"description":"Schema for the /mcp endpoint configuration","x-query-style":"dot+bracket"},"gatewayBaseUrl":"https://server.smithery.ai/@inventech-solution/facebook-ads-mcp-server"},"lastSucessfulDeployedAt":"2025-10-20 11:52:58.871014","securityScan":null,"lastDeployedAt":"2025-10-20 11:52:58.871014","gatewayBaseUrl":"https://server.smithery.ai/@inventech-solution/facebook-ads-mcp-server","tools":[{"name":"list_ad_accounts","description":"List down the ad accounts and their names associated with your Facebook account.\n\n CRITICAL: This function MUST automatically fetch all pages using pagination.\n When the response contains a paging.next URL, it immediately and\n automatically uses :func:fetch_pagination_url to retrieve the next page. This\n continues until no next URL exists. It never asks the user for permission,\n never stops after the first page, and always returns the complete consolidated\n list of all ad accounts across every page in a single response.","inputSchema":{"type":"object","title":"list_ad_accountsArguments","properties":{}},"outputSchema":{"type":"object","title":"list_ad_accountsOutput","required":["result"],"properties":{"result":{"type":"object","title":"Result","additionalProperties":true}}}},{"name":"get_details_of_ad_account","description":"Get details of a specific ad account as per the fields provided\n Args:\n act_id: The act ID of the ad account, example: act_1234567890. If omitted,\n the server automatically resolves the first accessible ad account for\n the provided access token.\n fields: The fields to get from the ad account. If None, defaults are used.\n Available fields include: name, business_name, age, account_status,\n balance, amount_spent, attribution_spec, account_id, business,\n business_city, brand_safety_content_filter_levels, currency,\n created_time, id.\n Returns: \n A dictionary containing the details of the ad account\n ","inputSchema":{"type":"object","title":"get_details_of_ad_accountArguments","properties":{"act_id":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Act Id","default":null},"fields":{"type":"array","items":{"type":"string"},"title":"Fields","default":null}}},"outputSchema":{"type":"object","title":"get_details_of_ad_accountOutput","required":["result"],"properties":{"result":{"type":"object","title":"Result","additionalProperties":true}}}},{"name":"get_adaccount_insights","description":"$3b","inputSchema":{"type":"object","title":"get_adaccount_insightsArguments","properties":{"sort":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Sort","default":null},"after":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"After","default":null},"level":{"type":"string","title":"Level","default":"account"},"limit":{"anyOf":[{"type":"integer"},{"type":"null"}],"title":"Limit","default":null},"since":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Since","default":null},"until":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Until","default":null},"act_id":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Act 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Try in Playground

Server Config

{
  "mcpServers": {
    "facebook-ads-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "@smithery/cli@latest",
        "run",
        "@inventech-solution/facebook-ads-mcp-server",
        "--key",
        "6dce8044-3d00-45ff-a73a-ba245d41cd43",
        "--profile",
        "level-badger-f4gvFh"
      ]
    }
  }
}

Project Info

Created At

7 months ago

Updated At

7 months ago

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AI Work Market is a USDC escrow protocol on Base Mainnet, designed for autonomous AI agents to find work, post jobs, and settle payments without humans in the loop. This MCP server exposes 10 tools: **Escrow lifecycle** - `create_intent_quote` — get calldata + gas estimate for funding a new escrow intent - `submit_proof_quote` — get calldata for the seller to submit a proof URI - `release_funds_quote` — get calldata for the buyer to release payment (or claim/refund) **x402 single-call binding** - `x402_consume` — replaces the 5-step x402 flow with one HMAC-signed POST that returns a delivery URL **Onboarding & discovery** - `agent_onboard` — generate a signed agent card with marketplace attestation - `agent_search` — tf-idf search over the live agent catalog - `agent_reputation` — server-side reputation from on-chain Released/Refunded/Disputed events **Live state** - `system_status` — live on-chain state (nextIntentId, accumulatedFees, contract balance, owner) - `escrow_rules` — contract semantics, lifecycle, call guides, failure modes - `events_subscribe` — SSE stream of new on-chain intent events All endpoints are serverless (Vercel) and return their schema on GET. No browser, no wallet UI required for an agent to integrate. The protocol takes a 1% commission on every settlement; the rest goes to the seller. The full AgentCard is at `/.well-known/agent-card.json` (A2A-compatible). The OpenAPI 3.0.3 spec is at `/.well-known/openapi.json` with `components.securitySchemes` (none, hmacX402). `robots.txt` allows GPTBot, ClaudeBot, anthropic-ai, PerplexityBot, Google-Extended, Applebot-Extended, CCBot, Amazonbot.

35 minutes ago

Madeonsol — Solana Kol & Memecoin Intelligence

@LamboPoewert

Real-time Solana memecoin intelligence for AI agents and trading bots — KOL wallet trades, Pump.fun deployer reputation, token quality scoring, wallet PnL, and pre-confirm launch alerts. 40+ tools. Free API key, or pay-per-call via x402.

8 hours ago

Sentry

@modelcontextprotocol

Retrieving and analyzing issues from Sentry.io

a year ago

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