"A GitHub server implementing the Model Context Protocol (MCP)" 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.

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.

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.

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.

MCP Server for the GitHub API, enabling file operations, repository management, search functionality, and more.

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 server that gives AI agents bounded, auditable access to propose changes to an Obsidian vault stored in GitHub, with per-agent expiring tokens, read/write/deny path policies, mutability rules, frontmatter checks, and human-reviewed proposal branches.

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.

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 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.

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

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.

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.

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.

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.

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