lumigo-copilot
Lumigo Copilot MCP server for IDE integration. Lets agents in VS Code (GitHub Copilot), Cursor, JetBrains, Eclipse, and Xcode investigate and resolve production issues from the editor via natural-language queries about errors, alerts, and root causes.
One-click install for Cursor, VS Code, Claude, and 20+ other MCP clients, powered by API Commons MCP Install — visit install.apicommons.org for more information.
Endpoint
Hosted endpoint · transport http
Connect
This is a remote MCP server — point an MCP client at the endpoint URL. Clients with native remote support (Claude, Cursor, VS Code, …):
For stdio-only clients (older Claude Desktop, etc.), bridge with mcp-remote:
If the server requires authentication, add the provider's token/header (e.g. an X-API-Key) per its docs. A quick reachability check:
Tool quality observed · not scored
tools with readOnly / destructive hints
parameters described (1 total)
state-changing tools without destructiveHint
tool-list tokens (1 tools)
tools over ~1,200 tokens
From an anonymous initialize + tools/list capture measured 2026-10-20; tokens are chars/3.6 of each tool definition. Recorded for the Kin Score's agent readiness as an observed signal — it contributes no points yet.
Tools
get_issue_details_from_lumigo— Retrieve detailed information about a specific issue using a free-text description. Use this tool whenever a user wants to get info or wants to get help fixing an issue. Pass any description that the user provides. For example, if the user says "Help me fix TypeError in my order-processor lambda", you can pass "TypeError in order-processor lambda" as the issue_description. Parameters: - issue_description (str): A natural language description of the issue (e.g., "I have a TypeError in my code"). Returns: A summarized report of the issue, including: - The error stack trace - A high-level explanation of the transaction that caused the error - Likely root cause (e.g., malformed input, timeout)
About MCP
The Model Context Protocol (MCP) is an open protocol Anthropic introduced for connecting LLM-based agents to external tools and data sources. Providers publish MCP servers that expose their API surface as structured, discoverable tools — an MCP-compatible client (Claude Desktop, Cursor, Cline, Continue, etc.) can connect to the server and call its tools without any per-provider integration code.
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Work with this as data
Every MCP server here is available over the APIs.io API and to AI agents over MCP.