"MCP server for accessing online documentation of open-source libraries in coding agents" matching MCP servers:

Provides MCP tools to search, retrieve, and answer questions from the public Open Finance Brasil Confluence documentation using BM25-based local indexing.

Enables full-text search and paginated retrieval of indexed documentation (PDFs, Markdown, text) through MCP tools, with filtering by category and file.

MCP server for searching, browsing, and analyzing decompiled Minecraft source code locally. Supports symbol lookup, text search, reference lookup, and lightweight RAG.

Local-first document management and semantic search for AI coding agents, with a built-in web dashboard and REST API.

Enables a local, read-only search over user-provided tabletop campaign source cards and module directories, routing queries to ranked hits across Markdown, JSON, and YAML text files while excluding core rulebook and SRD content by default. Returns file-and-line pointers with small context windows, plus explicit private-source opt-in, so a game master can locate and open the exact passage in their own library.

Enables AI agents to search and query documentation from git repositories using hybrid search and structured metadata queries.

Enables Codex to rank available tools and skills, rerank code and documentation search results, and triage saved output artifacts using Jev-based relevance scoring while leaving final decisions to Codex.

Local MCP server for specialist personas, reusable Markdown workflows, task-scoped subagent contracts and per-repository memory. Runs on your own computer with Python 3.11+ and a locally installed embedding model; its Claude Code plugin launches that separate installation.

Shrimp Task Manager is a task tool built for AI Agents, emphasizing chain-of-thought, reflection, and style consistency. It converts natural language into structured dev tasks with dependency tracking and iterative refinement, enabling agent-like developer behavior in reasoning AI systems.

Enables multiple MCP agents to read and write a single user-controlled, local-first fact layer under one user identity with explicit scopes, preserving sources, versions, permissions, and audit history. Supports structured memories such as preferences, facts, task state, and decisions, plus structured handoff capsules so one agent can resume another's work by task ID.

Enables AI assistants to search local codebases semantically by meaning, automatically indexing code and returning relevant chunks even when terminology differs. It also supports package version lookup, workspace switching, reindexing, cache clearing, and server status checks.

Enables AI coding agents to search and read local Markdown knowledge bases generated by Agent Docs for Markdown, across single or multiple workspaces, including link/backlink discovery and index status checks.

Enables AI assistants to search a codebase by meaning rather than exact keywords by indexing files with local AI embeddings, alongside package-version lookup and index management tools. It supports incremental, resource-throttled indexing across multiple workspaces and IDE integrations.

Enables AI coding assistants to search a local codebase semantically using AI embeddings, finding relevant code by meaning instead of exact keywords. It also provides package version lookup, manual reindexing, cache clearing, workspace switching, and server health status tools.

Enables AI assistants to search a codebase by meaning using local AI embeddings, finding relevant code even when terminology differs from the query. Also provides package version lookup across 20+ registries, workspace switching, reindexing, cache clearing, and status checks.

Exposes a standardized web search tool via Brave Search for MCP clients like Codex, Claude, and Cursor, returning stable JSON.

Enables AI assistants to search code by meaning using local AI embeddings, and provides package version lookup, reindexing, cache management, workspace switching, and server status tools.

Enables AI coding assistants to find relevant code by meaning through local AI embeddings and an indexed codebase, so searches work even when terminology differs. It also supports package-version lookup, reindexing, cache management, workspace switching, and server status checks.

Enables AI coding assistants to search codebases by meaning using local AI embeddings, with tools for indexing, cache and workspace management, status checks, and latest package-version lookup.

Enables AI assistants to search a codebase by meaning using locally generated embeddings, so relevant code is found even when the query's wording differs from the code. It also supports package version lookups across many ecosystems, plus reindexing, cache clearing, workspace switching, and server health checks.