"Local small language model for filesystem and network tasks" matching MCP servers:

Provides local hybrid search over files by combining semantic vector and full-text BM25 retrieval, with MCP stdio/HTTP support, OAuth 2.1 authentication, and tools for reading and converting documents to Markdown.

An MCP server that retrieves and provides AI model information from OpenAI, Anthropic, and Google through a unified interface.

MCP server for Topaz switches: searches documentation, performs network diagnostics (ping, traceroute, port scanning, etc.), calculates subnets, and generates VLAN/base configurations. Also includes a web UI for use without an MCP client.

An MCP server that turns the Hugging Face Hub into a conversational model picker with a tool-use eval harness to prove the agent actually uses it correctly.

Privacy-first local document search using semantic search. Runs entirely on your machine with no cloud services, supporting PDF, DOCX, TXT, and Markdown files.

A local-first document retrieval MCP server that enables AI coding tools like Codex to search private local documents via semantic search and keyword boost, supporting ingestion of PDF, DOCX, TXT, Markdown, and HTML files.

A fully local RAG MCP server for semantic code search and code intelligence, using AST-level chunking and hybrid search to pinpoint functions, classes, and APIs. No cloud, no API keys, zero setup.

A local-first MCP server for PageIndex — the vectorless, reasoning-based RAG framework. It lets local AI agents index and query local PDF and Markdown documents through a self-hosted PageIndex installation, without requiring any PageIndex cloud API key.

Local-first temporal knowledge graph with six read-only MCP retrieval tools. Supports Ollama and embedded LadybugDB; additions use a separate CLI proposal queue with human approval and explicit application.

Enables MCP clients to administer a local LM Studio instance: loading, estimating, downloading, configuring and unloading models, running chat and embedding inference, diagnosing the server, engines and hardware, and managing MCP connectors with conflict-safe configuration. It also builds a local document index supporting citation-checked search and answers grounded in TXT, Markdown, PDF and DOCX files.

Provides fully local long-term memory for AI agents by enabling semantic search over notes and session logs using Ollama embeddings, with no external APIs or databases.

Enables AI assistants to perform semantic, hybrid, and filtered search on indexed local documentation with RAG capabilities.

A local-first MCP server for indexing and searching codebases using PostgreSQL and Ollama embeddings, ensuring complete privacy and zero API costs.

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

Enables read-only semantic search over a local document corpus with on-device embeddings and a local Chroma store, featuring symlink-hardened file access and structured error handling.

Provides persistent long-term memory and local RAG document search for Claude Desktop, fully offline. Enables memory save/search and document retrieval via MCP.

A Model Context Protocol server implementing Graph RAG with local, embedded Knowledge Graph using FAISS for vector search and NetworkX for graph traversal, enabling hybrid retrieval through anchor discovery and relationship expansion.

Local-first realtime web research MCP for LM Studio with keyless SearXNG, clickable citations, adaptive deep research, provider health, and one-click Windows startup.

A lightweight, powerful local memory server for AI agents supporting text, entities, and relations. Enables persistent codebase understanding and user preference management.

Provides a standardized protocol for tool invocation, enabling an AI system to search the web, retrieve information, and provide relevant answers through integration with LangChain, RAG, and Ollama.