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

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

First gitlab mcp for you, building together

Enables interaction with self-hosted LLM models via Ollama and Supabase database operations. Supports text generation, SQL queries, and data storage/retrieval through natural language commands.

A fully offline MCP server for token estimation, prompt compression, model routing, and semantic caching to optimize LLM usage costs and efficiency.

Local workspace memory for Claude Desktop. Indexes documents into a vector store with hybrid search, cross-session memory, auto-learn, and knowledge graph.

A tool that creates MCP (Model Context Protocol) servers from OpenAPI/Swagger specifications, enabling AI assistants to interact with your APIs.

A self-contained Claude Code plugin that profiles a project by running a fixed DAG to emit agent-facing context pages, a human/developer guide, and a queryable vectorstore.

Perplexity AI search, reasoning, research, and compute - MCP server, dashboard, and multi-IDE auto-config for VS Code.

Enables coding agents to retrieve compact, cited repository maps through MCP tools such as search, symbol inspection, flow investigation, and deep context loading.

Stores manual project memories, enables semantic retrieval, and tracks per-memory confidence using PostgreSQL with pgvector and OpenAI-compatible embeddings.

Enables users to interact with an e-commerce shopping assistant using natural language to search products, check prices and ratings, compare items, and get personalized recommendations.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

A Python MCP server that gives LLMs persistent, searchable access to project context — documentation, architecture decisions, and session notes.

Enables document Q&A with grounded citations using the official Gemini File Search API. Upload documents, create stores, and ask questions that return exact passage citations.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

Hardware-accelerated codebase mapping that indexes Git repositories into Postgres/pgvector and serves code search, relationships, and static analysis results via a stdio MCP server.

It enables users to interact with a codebase through hybrid retrieval, code graph navigation, impact analysis, and context preparation for AI coding agents.

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Reckon Accounts Hosted (beta): https://www.cdata.com/download/download.aspx?sku=KHZK-V&type=beta

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

Enables hybrid retrieval-augmented generation with semantic and keyword search over documents, supporting multiple formats and providing MCP integration for Claude Desktop.