"Analyzing user contributions to a GitLab self-hosted project using API token" matching MCP servers:

Converts any REST API into MCP-compatible tools instantly by providing an OpenAPI/Swagger spec, enabling seamless integration with AI agents.

Acts as a bridge between standard REST/OpenAPI web APIs and the Model Context Protocol, dynamically converting REST endpoints into MCP tools for LLM clients like Cursor, Claude Desktop, and n8n.

Automatically converts OpenAPI/Swagger documents into MCP servers, enabling AI agents to call third-party REST APIs via the MCP protocol.

Discovers LLM models in real time from cloud providers and local Ollama instances, returning compatibility profiles and live pricing so AI agents can route tasks to the cheapest viable model without breaking tool calls or context clipping.

Enables AI coding agents to conserve tokens by enforcing rules like delegating heavy work to subagents, checkpointing before token limits, and grepping before reading files.

A self-hosted remote MCP server for cross-model AI session handoff, allowing users to start a project in one AI assistant and continue in another via shared project logs, files with version history, and full-text search, all stored in a single SQLite file on their own server.

Enables Cursor to reach any number of child MCP servers through just five host tools and a staged catalog, so tool schemas stay off the host until a specific tool is needed and token spend stays low. Searches tool names, pulls a single schema on demand, then invokes it, while disabled children consume zero processes and zero schemas.

Enables AI agents to control a browser with self-healing locators that automatically recover when selectors change, allowing reliable web automation through natural language.

Enables autonomous learning from interactions through pattern recognition and machine learning techniques. Continuously improves performance by analyzing tool usage, providing predictive suggestions, and sharing knowledge across MCP servers.

Enables coding agents in different editors and MCP clients to share messages, project context, notes, task ownership, handoffs, and advisory file claims through a local SQLite-backed coordination server. Supports MCP stdio, MCP Streamable HTTP, a JSON HTTP API, and a local CLI for multi-project agent collaboration.

Enables AI agents and human managers to orchestrate GitHub-based project work by self-assigning tasks, coordinating swarms, tracking token budgets, generating PRDs, planning sprints, triaging issues, and materializing tasks as GitHub issues, milestones, and project views.

Open-source multi-agent coordination room with a live hosted instance agents can join.

Enables AI coding agents to request a second opinion from a different frontier model via a single tool call, with PII scrubbed before transit, live web search, and support for Claude, ChatGPT, Cursor, and Gemini.

Enables AI agents to request an independent second opinion from a different frontier model, with PII scrubbing before transit, live web search grounding, caching, and multi-provider failover.

Enables AI agents to cut token usage by locally pruning, encoding, and summarizing MCP tool responses, with lossless recovery of original data when needed.

Enables high-throughput API rate limiting with deterministic token bucket throttling and burst quota management for AI agents.

Enables ChatGPT to ask users for decisions or clarification through native question cards with options and free-text input, then continue the task after the user responds.

Installs once in Claude Code and automatically discovers the nearest project's mcp.json, launching that checkout's declared MCP servers and forwarding their tools, resources, and prompts through a single connection. Each session keeps its own isolated connections, so repositories can ship their own local server manifests without maintaining a global configuration.

MCP server that enables AI assistants to run multi-step agent pipelines (e.g., Issue Analyst → Code Writer → Test Runner → PR Opener) from conversations, with support for Devin, shell, Python, and HTTP agents.

Enables AI coding agents to self-assign, coordinate, review, and ship work through GitHub Projects v2, with AI-powered PRD generation, sprint planning, issue triage, and token-budget enforcement.