OpenMemory MCP Troubleshooting Guide

Repository management, file operations, and GitHub API integration

Conduct comprehensive research projects using a virtual computer equipped with a real browser, coding tools, document creation capabilities, and more. Deep Research by Openhelm enables your agent to tackle work such as: • Market and competitor analysis • Industry and company research • Investment and acquisition due diligence • Technical and scientific investigations • Report generation with sources and evidence What makes OpenHelm the best solution for this: • Research is continuously reviewed and refined by a powerful AI to maximise accuracy and completeness • Uses a highly capable stealth browser that can access more of the web than traditional research agents • Multi-step workflows allow findings to be validated, expanded, and synthesised automatically • Generates structured outputs rather than simply returning search results For high-stakes research that requires depth, accuracy, and persistence, OpenHelm provides a secure remote environment where complex investigations can be completed autonomously.

AI image generation using various models

An MCP server implementation that provides a tool for dynamic and reflective problem-solving through a structured thinking process.

Model Context Protocol server that integrates AgentQL's data extraction capabilities.

summarize chat message

Location services, directions, and place details

GitLab API, enabling project management

A Model Context Protocol (MCP) server for image generation and manipulation using fal.ai's Stable Diffusion model.

Control your Instagram from Claude — publish photos, reels, carousels, read insights, manage comments and DMs. 14 tools via Instagram Login API. One-click free Render deploy for Claude Web and mobile.

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)

Retrieving and analyzing issues from Sentry.io

Create a remote sandbox that can execute code/run commands/upload and download files. 创建远程沙盒，可以执行代码/运行命令/上传下载文件

A Model Context Protocol server that provides time and timezone conversion capabilities. This server enables LLMs to get current time information and perform timezone conversions using IANA timezone names, with automatic system timezone detection.

A Model Context Protocol (MCP) server that integrates with Jina AI Search Foundation APIs.

Use TradeOS MCP Server to bring your trading data, indicators, strategy logic, and agent workflows into MCP-compatible AI tools. Copy your server URL, add it to GPT or Claude, and let your AI assistant work directly with your TradeOS trading intelligence.

Local-first FinOps copilot: ask about your AWS, Azure, GCP, and SaaS costs in plain English. Anomaly detection, rightsizing, idle-resource cleanup, and Jira/Linear ticketing, all in your own Claude. Credentials never leave your machine.

AgentDrive is a cross-agent artifact workspace with provenance and portable storage across Claude Code, Codex, Cursor, and LangGraph. 20 MCP tools: file CRUD, semantic recall over workspace artifacts, run logging, cross-agent attribution, comments, and shares. Connect to the hosted server at https://mcp.agentdrive.sh/mcp with an Authorization: Bearer key, or run locally via npx @adrive/mcp-server. Free tier (1 GB + 10k embeddings) at https://app.agentdrive.sh — no credit card.

Connect your AI assistant to IndoTender — Indonesian government procurement data via the Model Context Protocol. Search LPSE tenders, procurement realisasi, company profiles, treasury payments, and government agency directories — all from your AI chat.

Improve your visibility across both traditional search engines and AI-powered answer engines using a virtual computer that can analyse websites, competitors, content, and search performance. SEO & GEO by OpenHelm enables your agent to carry out work such as: • SEO audits and recommendations • GEO (Generative Engine Optimisation) analysis • Competitor monitoring • Content opportunity discovery • Search visibility reporting What makes OpenHelm the best solution for this: • Continuously evaluates whether recommendations are actually improving visibility over time • Can investigate competitors and search results using a highly capable stealth browser • Multi-step workflows allow analysis, planning, implementation, and monitoring to work together • Designed for both search engines and emerging AI discovery platforms For organisations looking to grow organic visibility, OpenHelm provides a secure environment where optimisation work can be performed continuously and autonomously.

The Milvus MCP server enables AI applications to interact with Milvus vector databases using natural language commands. It allows AI models to perform vector searches, manage collections, and retrieve data without writing custom database queries. This integration facilitates seamless access to vector data, enhancing the capabilities of AI tools like Claude Desktop and Cursor.

A universal gateway MCP server providing seamless integration with multiple AI models and services through a unified interface.

LADU’s MCP server connects AI assistants directly to LA County ADU data. Ask about any address and get a plain-English buildability verdict, the parcel’s zoning and regulatory overlays (hillside, coastal, fire, flood, historic, fault zones), and the governing city’s ADU rules. Query permit statistics for any of 51 supported LA cities — totals, year-over-year trends, and valuation distributions from 19,000+ cleaned permit records going back to 2018. Compare two cities side by side, estimate project costs by type and finish level, or find permitted ADUs near an address.

TickDB MCP provides AI assistants with unified real-time and historical market data across Forex/FX, US/HK/A-share stocks (NASDAQ, NYSE), crypto, indices, and precious metals (XAU/XAG). 13 tools cover real-time quotes, ticker, order book depth, recent trades, and OHLCV candlestick (K-line) data over 37,527+ symbols. Powered by the TickDB unified market data API.

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.