"semantic-release" matching MCP servers:

Exposes WAI-ARIA Authoring Practices Guide (APG) patterns, providing narratives, keyboard guidance, and official source code examples for accessible widgets. It includes tools for listing patterns, retrieving specific specs, and performing semantic searches via Ollama.

Redmine for AI agents (Claude Code, Cursor, Copilot): search and read issues, projects, members, versions, wiki, time entries and reference data; extract text from attachments (PDF, DOCX, XLSX, ZIP); analytics such as release risks, blocker chains and stale issues. 32 read-only tools by default, 7 optional write tools. Java, stdio, Docker image available.

Git-native long-term memory for AI agents: your markdown files are the source of truth, the search index is a disposable projection rebuilt from git, and every memory the agent writes is a reviewable git commit. Served over one OAuth-secured MCP endpoint with hybrid lexical+semantic recall and a gated, git-first commit_note write tool.

Enables AI assistants to turn local git history into answers about recent activity, file hotspots, change coupling, stale or already-merged branches, contributors, ref comparisons, and drafted release notes. It runs locally over stdio with a git subcommand allowlist, so it is read-only, works offline and without shell access, and is safe to auto-approve.

Enables querying and analyzing humanitarian data, such as refugee statistics, through semantic tools like country comparisons, trend analysis, and report generation, using the UNHCR API.

Unified MCP orchestration layer that consolidates multiple MCPs into a single interface with semantic tool discovery, code-mode execution, scheduling, and intelligent caching to reduce token usage by 97% and eliminate choice paralysis.

Enables MCP-capable IDEs to search 8,214 design-system components, retrieve exact source bundles and semantic tokens, and follow a copy-first handoff workflow with composition validation.

Enables file-based knowledge management with ranked keyword and semantic hybrid search, allowing AI agents to learn from documents and recall relevant knowledge as a persistent memory tool.

Enables AI agents to interact with the Moltbook social network, including posting, reading feeds, commenting, voting, and semantic search.

A production-grade MCP server providing an autonomous AI agent swarm, persistent semantic memory, browser automation, multi-model reasoning, and 78+ tools for AI-first testing and development.