Packages

Query OpenAI models directly from Claude using MCP protocol.

Provides an MCP (Model Context Protocol) server exposing Quay container registry functionality as dynamically generated MCP tools. It auto-discovers relevant Quay API endpoints from Quay’s OpenAPI specification, supports parameter mapping, and optionally authenticates using an OAuth token.

A MCP server to connect to wolfram alpha API.

semantic-router is a Python decision/routing layer that selects a route (e.g., intent, task, tool-use path) by embedding the incoming utterance(s) into a vector space and matching them against route utterance embeddings, returning the best-matching Route (or None if no match). It supports multiple encoder backends (e.g., OpenAI, Cohere, Hugging Face, FastEmbed, local/HF+Torch/llama-cpp) and can integrate with vector indexes such as Pinecone and Qdrant; it also advertises multimodal routing via optional vision/multimodal paths.

mcp-name: io.github.ysydhc/team-memory

MCP server to pull status from Linear

An open-source “MCP Registry & Gateway” that lets clients discover and execute Model Context Protocol (MCP) servers through a unified HTTP API. It supports bridging STDIO-based local MCP servers and remote Streamable HTTP servers, includes a sandboxed execution model, and provides an OAuth 2.1 proxy. It also exposes a publicly hosted registry dataset/index via JSON for programmatic discovery (data-only usage).

A Model Context Protocol (MCP) server for accessing Data Commons API data.

This is a POC of how you can build an MCP servers on top of Uber Eats

Provides an MCP server that lets an AI client (e.g., Claude Desktop) call Upstage document digitization and information extraction APIs to parse documents (PDF/images/Office files) and extract structured fields based on schemas.

PostgreSQL-backed tool that transforms compressed Reddit/Voat/Ruqqus data dumps into searchable HTML archives with full-text search, REST API, and an MCP server with 29 tools for AI assistant integration.

AgentSeal is a local-first security toolkit/CLI and Python/TypeScript library for auditing AI agent configurations and prompts. It scans for dangerous “skill”/agent files, checks MCP server/tool configurations for poisoning, analyzes toxic data flows, provides prompt red-teaming via adversarial probes, and can continuously watch/alert on changes to agent config files.

An MCP server that lets an AI coding assistant search and fetch Apple Developer Documentation (symbols, articles/guides, and specific doc paths) using MCP tools such as discover_technologies, choose_technology, search_symbols, get_documentation, and get_version.

Provides an MCP server that bridges Claude Desktop/Claude Code to the Chrome DevTools Protocol (CDP), enabling LLM-driven browser debugging such as starting/connecting to Chrome, navigating pages, inspecting DOM and JS objects, monitoring network traffic and console output, and collecting performance/storage data.

codemogger indexes local source code by parsing it with tree-sitter, chunking into semantic units, embedding chunks with a provided/local embedding pipeline, and storing vectors plus full-text search in a single embedded SQLite (.db) file; it also provides an MCP server and CLI for indexing/reindexing and searching that index.

Provides a local JSON-backed memory store for context engineering with GitHub Copilot and MCP clients. Includes a CLI REPL to add/search/compress/delete/purge/export memories, and an MCP stdio server exposing tools and resources to let Copilot agents read/write/search memories and inject shaped/compressed context for tasks (optionally using DeepSeek for summarization/context shaping).

deepeval is an open-source Python framework for evaluating LLM apps (e.g., chatbots, agents, RAG pipelines). It provides a test/pytest-like workflow and many ready-to-use evaluation metrics (including LLM-as-a-judge metrics such as G-Eval, RAG metrics, agent/tool metrics, multimodal metrics). Metrics can run locally (using the chosen models) and it can integrate with CI/CD and common LLM app frameworks (OpenAI, LangChain, LangGraph, LlamaIndex, CrewAI, etc.). It also offers a hosted “Confident AI” platform option with CLI login and a stated MCP server integration for persisting data/traces.

Agentify Desktop is a local-first Electron desktop app that connects your logged-in AI web sessions (e.g., ChatGPT, Claude, Gemini, Perplexity, etc.) to an MCP-compatible CLI client. It manages real browser tabs/windows (embedded Electron or Chrome CDP), supports file upload and saving/downloading artifacts, and exposes MCP tools to create/reuse tab keys, read page transcripts, and run automated workflows with human-in-the-loop CAPTCHA handling.

electron-mcp-server is an MCP (Model Context Protocol) server that automates and observes Electron applications. It can launch Electron apps with debugging enabled, inspect window/target information via Chrome DevTools Protocol, take screenshots via Playwright/CDP, stream Electron logs, build apps, and execute various UI interaction commands (including selector/text-based clicking, form filling, screenshots, and an eval-style command gated by security settings).

js-reverse-mcp is an MCP server (TypeScript) that drives a Chrome/Chromium instance to help AI coding assistants inspect and debug JavaScript in web pages. It supports page navigation/context selection, script listing and source retrieval, breakpoints/stepping, function tracing, runtime evaluation at breakpoints, and network/WebSocket inspection. It also supports pre-load script injection. The project documentation highlights use of a stealth/anti-detection browser engine (Patchright) with many stealth settings.