MCP server for US immigration guidance — live Visa Bulletin, priority date checker, and immigration term explanations powered by official government data
A TypeScript server implementing the Model Context Protocol that provides secure code execution in isolated Docker containers, allowing LLM applications to safely run Python, Go, or JavaScript code snippets.
An MCP server for codebase context that gives AI coding agents structural understanding through symbol graph, semantic search, blast radius, and convention detection tools.
Enables AI agents to maintain Git-backed long-term project memory over MCP, supporting on-demand retrieval, curated writes, conflict-safe versioning, idempotency, and crash recovery so new sessions or machines can recover context and continue working.
Provides AI assistants with persistent graph database memory using Neo4j, enabling task management, relationship understanding, semantic search with embeddings, file indexing, and multi-agent coordination through the Model Context Protocol.
https://gopls-mcp.org/
MCP server for golang projects development: Expand AI Code Agent ability boundary to have a semantic understanding and determinisic information for golang projects.
Official MCP server for Skycloak (managed Keycloak) that enables managing clusters, realms, applications, identity providers, users, themes, exports, SIEM destinations, and webhooks through natural language, with OAuth or API key authentication.
Keeps Jira Cloud, Jira Server, Linear or its own built-in tracker (plus Confluence pages) in one local SQLite file. Its MCP tools answer from that file: read-only SQL, full-text search across issues, comments and wiki pages, issue detail, sprint and retro reads.
Minimal long-term memory MCP server for AI assistants backed by SQLite FTS5 full-text search, optional hybrid vector retrieval, scoped memory graphs, and VSCode extension.
Lets AI agents see and control desktop applications through the accessibility layer, enabling clicking, typing, scrolling, dragging, and window/app management across macOS, Windows, and Linux entirely on the local machine.
Runs a language server and provides tools for communicating with it. Language servers excel at tasks that LLMs often struggle with, such as precisely understanding types, understanding relationships, and providing accurate symbol references.
Enables LLM agents to maintain structured long-term memory and knowledge using SQLite, with graph storage and relational query tools for persistent context.
Enables agents to store documents and atomic facts with provenance in a local SQLite knowledge base, then search them through fused keyword, exact, semantic, entity, graph and fact retrieval arms that return one ranked list where every result carries its address, trust level and a reason for its rank. A read-only terminal and loopback web view let humans inspect the same searches, timelines, entity neighbourhoods and agent-written pages without being able to alter the knowledge base.