AI tools for “mcp”

Guide for using Apollo MCP Server to connect AI agents with GraphQL APIs. Use this skill when: (1) setting up or configuring Apollo MCP Server, (2) defining MCP tools from GraphQL operations, (3) using introspection…

Build, deploy, and secure Model Context Protocol (MCP) servers on Netlify. Use whenever the task involves creating an MCP server, exposing an app or API to AI agents as MCP tools, letting Claude / Cursor / Claude Code…

Instrument an MCP server with Pendo MCP analytics in Python, TypeScript, Go, or Java. Detects which language/SDK the server is built with and wires up the matching Pendo integration — PendoMCPServer (Python), initMcp()…

Reference for the Pinecone MCP server tools. Documents all available tools - list-indexes, describe-index, describe-index-stats, create-index-for-model, upsert-records, search-records, cascading-search, and…

Configure safe agent behavior around PlanetScale MCP, Insights, schema recommendations, and repository work without autonomous production mutation.

Starting point for exploring how a PostHog MCP server's tools are used — routes a broad question to the typed tool that answers it. Use when the user asks "how is my MCP doing?", "what should I look at?", "explore my…

Build a starting-point taxonomy for an MCP tool — what users were trying to accomplish before they reached the tool — and publish it as a PostHog notebook. Reconstructs each session's goal from its opening tool calls,…

Investigate the quality of PostHog MCP tool calls — error rates, latency, reach, and which tools are failing or slow. Use when the user asks "which MCP tool has the highest error rate?", "what's the slowest tool?",…

Investigate individual PostHog MCP sessions — the sequence of tool calls a single agent made in one run, what it was trying to do, and where it went wrong. Use when the user asks "what did this MCP session do?", "show…

Explore PostHog MCP intent clusters — agent goals grouped by semantic similarity, with each cluster's tool distribution and error rates, plus the tool-centric pivot (capture rate per intent, discovery rate against the…

Signals scout for PostHog MCP tool calls. Watches `$mcp_tool_call` telemetry for tools that need improvement — broad-reach failure rates, retry hammering, slow or context-bloating responses — grouped by owning product…

Troubleshoot Superset MCP health, validation, permission, response-size, and bug-report workflows. Use only for MCP tool workflows; do not use for direct API work.

Use Superset MCP tools for Explore links, chart configuration discovery, chart previews, saved charts, and chart updates. Use only for MCP tool workflows; do not use for direct API work.

Route Superset MCP tool workflows, source-of-truth checks, and surface-boundary decisions. Use only for MCP tool workflows; do not use for direct API work.

Connect to and use the hosted Preset MCP gateway, choose between the aggregate gateway and a direct workspace Superset MCP connection, and run the list_workspaces, search_workspace_tools, call_tool flow. Use only for…

Use Superset MCP health, instance, list, detail, schema, and chart-type discovery tools. Use only for MCP tool workflows; do not use for direct API work.

Use Superset MCP tools for SQL execution, SQL Lab links, and saved SQL queries. Use only for MCP tool workflows; do not use for direct API work.

Use Superset MCP tools for dashboard inspection, dashboard creation, and adding charts to dashboards. Use only for MCP tool workflows; do not use for direct API work.

Use Superset MCP data-returning tools for chart data, chart previews, rendered chart SQL, and dataset query results. Use only for MCP tool workflows; do not use for direct API work.

Use Superset MCP tools for dataset inspection, semantic-layer querying, and virtual dataset creation. Use only for MCP tool workflows; do not use for direct API work.