Machbase Neo Mcp Server

Created By
machbase10 months ago
Overview

What is Machbase Neo MCP Server?

Machbase Neo MCP Server is a server that facilitates natural language-based database operations by integrating Claude Desktop with Machbase Neo, allowing users to perform database tasks using simple language commands.

How to use Machbase Neo MCP Server?

To use the server, install Claude Desktop, clone the Machbase MCP Server repository, and run the installation script. After installation, you can make natural language requests through Claude Desktop to interact with the Machbase Neo database.

Key features of Machbase Neo MCP Server?

  • Natural language to SQL conversion for database operations.
  • Real-time integration with Machbase Neo for data manipulation and querying.
  • AI-powered explanations and documentation search.
  • Native integration with Claude Desktop without needing additional API keys.

Use cases of Machbase Neo MCP Server?

  1. Creating and managing time series databases for IoT sensor data.
  2. Executing complex SQL queries through natural language commands.
  3. Searching and retrieving information from Machbase documentation.

FAQ from Machbase Neo MCP Server?

  • Can I use natural language for all database operations?

Yes! You can perform various operations like creating tables, inserting data, and querying information using natural language.

  • Is there a need for additional API keys?

No, the server integrates directly with Claude Desktop, eliminating the need for extra API keys.

  • What types of data can I analyze?

You can analyze time series data, including IoT sensor data and log data.

Server Config

{
  "mcpServers": {
    "machbase": {
      "command": "C:/Users/Username/anaconda3/envs/mcp/python.exe",
      "args": [
        "C:/Users/Username/AppData/Roaming/Claude/Machbase.py"
      ],
      "env": {
        "MACHBASE_HOST": "localhost",
        "MACHBASE_PORT": "5654"
      }
    }
  }
}
Project Info
Created At
10 months ago
Updated At
10 months ago
Author Name
machbase
Star
-
Language
-
License
-

Recommend Servers

View All
Bring your real authenticated browser session to AI coding agents. Local-first MCP server + Chrome MV3 extension. No cloud. No telemetry.
@Cubenest

peek records the user's actual logged-in browser (DOM via rrweb, console events, network metadata, optional response bodies via opt-in Deep capture) through a Chrome MV3 extension. The extension ships events through a native-messaging stdio bridge to a local MCP server (peek-mcp), which persists them to a SQLite database at ~/.peek/sessions.db. AI coding agents (Claude Code, Cursor, Cline, Windsurf) read sessions from the database via 10 MCP tools: Tool What it does list_recent_sessions List recently recorded sessions (id, origin, ts, event count). get_session_summary LLM-readable narrative summary of a session. get_session_console_errors Console errors recorded in a session. get_session_network_errors Failed/notable network requests in a session. get_user_action_before_error Last N user actions before a console error. generate_playwright_repro Generate a runnable Playwright test from a session. get_dom_snapshot Reconstruct the DOM at a given timestamp. query_dom_history Timeline of attribute/text changes for a selector. request_authorization Side-panel consent for write actions (Level 3). execute_action Dispatch a UI action (gated by permission level + destructive blocklist). Why local-first matters Every other "browser session for AI" tool ships to a vendor cloud. peek's SQLite + extension live on the user's machine — no remote endpoints, no telemetry. The privacy policy (docs/peek/PRIVACY_POLICY.md) is the source of truth. Install # 1. Add the MCP server to Claude Code claude mcp add peek -- npx -y @peekdev/mcp # 2. Install the Chrome extension from the Chrome Web Store # (link added once the CWS listing is approved)

a day ago
Tavily Mcp
@tavily-ai

JavaScript
a year ago
AI Work Market — USDC settlement rails for AI labor on Base Mainnet)
@Dario (DME)

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.

8 hours ago