"How to create GitHub projects, milestones, and issues" matching MCP servers:

MCP server that ingests PDF documents into pgvector for semantic search and RAG pipelines. It handles extraction, chunking, local embeddings, and storage, enabling agents to make PDFs searchable via natural language.

A lightweight RAG system that provides an MCP server for searching and interacting with vector-based knowledge bases. It enables users to perform retrieval-augmented generation and search across Qdrant collections through a standardized interface.

Semantic skill-library search MCP server that finds relevant skills or Markdown knowledge files from local directories using embeddings, SQLite vector storage, and Reciprocal Rank Fusion.

Semantic memory for AI builders: capture the tacit engineering know-how that never reaches your docs, recall it the moment it applies. Built in Rust on Postgres and pgvector.

RAG MCP server for PDFs, YouTube, GitHub repos, and Discord exports. Index documents and query with citations via LangChain and Chroma.

A server that provides data retrieval capabilities powered by Chroma embedding database, enabling AI models to create collections over generated data and user inputs, and retrieve that data using vector search, full text search, and metadata filtering.

Provides Claude Code read-only access to PostgreSQL for relational queries, schema inspection, EXPLAIN plans, pgvector similarity searches, and Apache AGE graph traversals.

Indexes codebases using semantic embeddings for natural language search, enabling developers to find code with queries like 'how does authentication work'.

Model Context Protocol server for RosalindDB, enabling AI clients to create datasets, ingest vectors, run similarity queries, and check usage on a cost-optimized vector search database.

A Model Context Protocol server for Chroma, enabling AI models to create collections and retrieve data using vector search, full text search, and metadata filtering.

An MCP server that streams K-line (candlestick) data from decentralized exchanges (DEXs) to power your AI agents and workflows.

Semantic memory MCP server that gives AI agents a self-writing, priority-based memory with local semantic search and automatic contradiction handling. It persists across sessions and projects, entirely on your machine.

Enables AI agents to interact with Milvus vector databases and Zilliz Cloud through natural language, allowing users to create clusters, manage collections, insert vector data, and perform semantic searches directly from their AI assistants.

Enables semantic code search across local projects and Git repositories using AI embeddings with ChromaDB. Supports both OpenAI and local Ollama models for private, enterprise-ready code analysis and similar code discovery.

Enables AI agents to autonomously create and manage topic-specific vector knowledge bases with end-to-end functionality including project creation, content ingestion from URLs, semantic search, and progress tracking. Provides a complete research workflow without exposing low-level APIs.

A server that provides access to Baidu Cloud Vector Database functionality through the Model Context Protocol, enabling LLM applications to perform vector searches and database operations via natural language.

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Enables Claude to store and query personal finance transactions using semantic search. Transactions are persisted in ChromaDB and JSON, allowing natural language questions about spending trends and portfolio allocations.

A persistent local vector memory server that allows users to store and search project-specific context using LanceDB and local embeddings. It enables MCP-compliant editors to maintain long-term memory across different projects without requiring external API keys.

Connects AI clients to MindsDB via the MySQL protocol to execute SQL queries, manage databases, and perform semantic searches within knowledge bases. It enables automated workflows through job scheduling and provides seamless integration with external data sources.