"Model Context Protocol (MCP) Servers Repository" matching MCP servers:

A unified context layer that connects your local data — repositories, documents, remote machines, and notes — to LLM interfaces through the Model Context Protocol (MCP).

Provides a standardized way to interact with MinIO object storage, allowing access to text files, binary files, and bucket contents while supporting operations like listing buckets/objects, retrieving objects, and uploading files.

Provides AI agents with secure, read-only file system access to analyze and understand project codebases, enabling multi-repository context aggregation and cross-project code tracing.

Enables agents to download single model weight files from Hugging Face repositories or Civitai model versions directly into allowlisted ComfyUI model folders. Source identifiers, destination categories, and file extensions are validated, and existing files are never overwritten.

MCP server that helps AI coding agents understand a repository by providing lightweight tree/map, code search, and token-budgeted context packing tools without dumping the entire monorepo into the prompt.

MCP server providing lossless file reads with deduplication, per-repo token metering, and HMAC-signed context receipts. Enables auditable, vendor-neutral measurement of what an AI agent saw.

Provides LLMs with secure, read-only access to local documentation by scanning directories, extracting content from PDF, DOCX, Markdown, and text files, and performing keyword searches.

A server that allows AI assistants to browse and read files from specified GitHub repositories, providing access to repository contents via the Model Context Protocol.

Enables local, bounded routing and evidence judgments for Codex tasks, with tools for reading file context, checking outputs, and selecting registered workflows while keeping execution and review with the client.

A Model Context Protocol (MCP) server that provides VSCode context and filesystem operations for AI assistants.

Enables MCP clients to inspect local Git repositories through five focused, read-only tools for repository trees, literal text search, numbered file reads, bounded git diffs, and project summaries while confining paths, skipping secret-like and binary files, and enforcing output limits.

This server provides an API to query Large Language Models using context from local files, supporting various models and file types for context-aware responses.

Enables ChatGPT to inspect a selected local project on demand, retrieving project overviews, code search results, file excerpts, and Git context without pasting entire repositories into the conversation.

A thin, local, read-only MCP gateway that exposes governed context documents and producer manifests as logical resources, enabling AI clients to access them without arbitrary filesystem access.

Enables AI agents to read, search, create, and append Markdown notes from a local vault (e.g., Obsidian) via MCP, allowing natural-language note management through compatible clients.

MCP server that gives AI chat real vision by reading images, files, logs, and zip archives via local OCR in any language, with privacy-first processing.

Enables AI coding agents to persist structured long-term memory (gotchas, architecture, API notes) in a .context folder and sync across devices and agents via Git.

Compress OCR-heavy PDFs into dense packed images so agents can work with long visual documents.

Enables managing personal information with dynamic topic-based organization (tasks, meetings, contacts, etc.), supporting optional OTP authentication and AES-256 encryption for sensitive data with automatic backups.

A simple MCP server for local documentation with RAG capabilities, enabling AI assistants to access and search local documents.

Enables Codex to gather bounded, read-only source evidence through literal search, optional file inventory, and exact line-range reads instead of automatically receiving entire files.

Provides a bulk_read_files tool that reads specified files and forwards them to a remote backend for summarization, so agents receive concise summaries instead of raw file contents.

MCP server providing filesystem allowlist and pack-aware Qdrant RAG search. Enables reading files, listing directories, and performing filtered RAG searches with case and pack IDs.

Efficiently loads, caches, and delivers project file context for AI agents using the Model Context Protocol, reducing multiple file reads to a single call with LRU caching and security validation.

Provides owner-bound secure storage and retrieval of tool outputs via MCP tools, enabling trusted persistence for agents like Claude Code, Codex CLI, and OpenCode.

Provides tools for file system operations and text generation using OpenAI-compatible models via the Model Context Protocol, supporting both stdio and HTTP transports.

A server implementation that provides a unified interface for OpenAI services, Git repository analysis, and local filesystem operations through REST API endpoints.

Enables AI assistants to read, search, and analyze local file systems with tools for reading file contents, listing directories, searching by patterns, and analyzing folder structures for context-aware queries.

A FastAPI-based JSON-RPC 2.0 server implementation that enables users to work with HDF5 files, submit Slurm jobs, retrieve CPU information, and visualize CSV data through standardized API endpoints.

Enables AI agents to interact with both frontend and backend projects by providing file system access and context through the MCP protocol, facilitating full-stack development assistance.