"Tool to analyze backend code, connect with Jira, and automate coding tasks" matching MCP servers:

A Docker-based local RAG backend that provides advanced document search capabilities using vector, graph, and full-text retrieval via the Model Context Protocol. It supports over 28 file formats and tracks evolving relationships between concepts using a Neo4j-backed graphiti implementation.

Enables AI assistants to search codebases by meaning using local AI embeddings, manage indexing and caching, switch workspaces, check server status, and look up latest package versions across multiple ecosystems.

Enables MCP-capable AI assistants to search and retrieve past Jira issues, resolutions, and recurring topics from a fully local embedded knowledge base using hybrid semantic and keyword search.

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 assistants to search codebases by meaning using local AI embeddings, along with package version lookup and runtime workspace, cache, indexing, and status management.

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.

Enables AI coding assistants to search a codebase by meaning using locally generated embeddings, so relevant code is found even when terminology differs from the query, along with package version lookup, reindexing, cache reset, workspace switching, and status tools. Indexing runs progressively in the background with CPU throttling and a SQLite cache, letting searches work immediately on large projects.

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 coding assistants to search codebases by meaning using local AI embeddings, and provides tools for package version lookup, reindexing, cache clearing, workspace switching, and status checks.

Enables AI assistants to perform semantic code search across local codebases using AI embeddings, with support for indexing, cache management, workspace switching, status checks, and 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.

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

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

Enables AI assistants to perform intelligent semantic code search across a codebase and provides auxiliary tools for package version lookup, reindexing, cache clearing, workspace switching, and server status checks.

Enables AI assistants to perform semantic code search across a local codebase by meaning rather than exact keywords, using local AI embeddings with flexible dimensions. It also provides indexing, cache management, workspace switching, package version lookup, and server status tools.

Enables AI coding assistants to search codebases by meaning using local AI embeddings, with tools for indexing, cache management, workspace switching, status checks, and package version lookup. It supports incremental and progressive indexing with configurable embedding dimensions to find relevant code even when terminology differs.

Enables AI coding assistants to search a codebase by meaning with local embeddings, manage indexing, cache, workspace configuration, and status, and look up latest package versions across multiple registries.

Enables AI coding assistants to search codebases by meaning using local AI embeddings, so they can find relevant code even when terminology differs, while also offering package version lookup, indexing, cache, workspace, and status tools.

Enables AI coding assistants to search a codebase by meaning using locally run AI embeddings instead of exact keyword matching, plus tools to look up the latest package versions, reindex, clear the cache, switch workspaces, and check indexing status.

Enables Claude to intelligently analyze and query codebases using knowledge graphs, supporting natural language code search, relationship discovery, and incremental updates.

MCP server scaffold that exposes stubbed tools for listing, searching, and summarizing sources, with built-in OAuth 2.1 authorization flow for Claude integration.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

An MCP proxy that embeds tool definitions and returns only the top-k semantically relevant tools per query, reducing context usage and routing calls to upstream MCP servers.

Enables semantic search over codebases using natural language queries, returning relevant code snippets with source locations. Integrates with Claude Code for automatic codebase exploration.

An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.

Enables AI coding assistants to semantically search codebases by meaning rather than exact text, with zero external daemons and fully local embeddings. Works out-of-the-box with Claude Code, Gemini CLI, Antigravity, and Cursor.