"semantic-release" matching MCP servers:

CNCF release intelligence: typed, quoted facts (security fixes, breaking changes, deprecations) from every graduated/incubating project's release notes, updated daily. check_stack compares running versions locally — versions never leave your process.

A server interface for Bitrise CI/CD platform that enables app management, build operations, artifact management, and release management through natural language interactions.

Neo4j MCP Canary is a fast-moving, experimental release of the Neo4j MCP server for customers who want to explore emerging capabilities before they are considered for the official server.

Local-first MCP server providing semantic search over library docs, fully offline. Single Go binary speaks MCP over stdio against a vector index pinned to the binary version. Like Context7 with the internet turned off. Apache 2.0. Linux + macOS, also available as a container image.

Provides persistent, searchable memory across AI coding agent and chat history (Claude Code, Codex, Gemini CLI, ChatGPT, and more) via retrieval-augmented generation, enabling semantic and hybrid search to retain context across sessions.

Search 419,000+ LLM-extracted space regulatory filings from the FCC, ITU, UNOOSA, and FAA. Semantic search, entity dossiers, spectrum-band holdings, launch licenses, filing trends, and alerts.

Lets AI agents drive terminal apps built with Limoni (a Go TUI engine) through their semantic tree instead of scraping the screen: widgets are found by role and label, clicked, typed into, and waited on. Runs locally over the app's automation socket; secret fields never reach the agent.

Self-hostable, markdown-native team wiki with a built-in MCP server: agents search, read, and write your wiki pages (ranked Postgres full-text + semantic search, backlink traversal). Plus Atlas, which auto-generates a cited, coverage-checked wiki from your git repos and Jira.

Persistent memory engine for AI coding agents. Single Go binary, zero runtime dependencies, MCP-native. Stores, searches, and deduplicates memories across sessions using embedded SQLite with hybrid FTS + semantic search, memory decay, relation graph, and token-budget context assembly.

Enables AI editors and agents to publish, search, subscribe to, and lint semantic messages across named namespaces, and to check broker connectivity and API key health.

MCP-native agent-to-agent messaging hub for AI swarms. Agents communicate via channels and DMs through MCP protocol — zero SDKs needed. Includes web UI, semantic search, analytics dashboard. Single Go binary, local-first.

A Model Context Protocol server enabling AI assistants to query and explore data warehouses via Trino, with optional semantic context from metadata catalogs.

An MCP server for semantic code search & navigation that helps AI agents work efficiently without burning through costly tokens. Instead of reading entire files, agents can search conceptually and jump directly to the specific functions, classes, and code chunks they need.

An MCP server for codebase context that gives AI coding agents structural understanding through symbol graph, semantic search, blast radius, and convention detection tools.

Exposes 30+ novel-writing tools over stdio or HTTP so external agents such as Claude Code or WorkBuddy can use their own models and API keys to read chapters, write prose, manage characters, foreshadowing, story arcs and worldbuilding, run local semantic search, and launch review sub-agents. Supports one-click enabling with configurable port, token, and approval mode.

Provides fully local, privacy-preserving semantic search over file names and paths via MCP, using BGE embeddings for fuzzy matching and supporting incremental updates, watch mode, and a loopback-only HTTP server.

An MCP server that enables controlled Xiaohongshu content publishing with an immutable review workflow, requiring explicit human confirmation before any release. It supports content generation, local editing, compliance recall, and one-time authorized posting, defaulting to generate-only mode.

self-hosted development harness (Go engine + CLI + desktop, Linux first) · brief → requirements → spec → plan → build → review → release · verdicts are exit codes, never model opinions · local models first (llama.cpp, vLLM) beside any OpenAI-compatible or Anthropic endpoint · operable by humans or by other agents over MCP with recorded, attributed decisions

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.

Enables MCP clients to submit bounded semantic-uncertainty judgments to the pinned TypeSafe Jev API, with tools for yes/no, choice, and score evaluations plus optional evidence or context selection.