"Semantic Scholar" matching MCP servers:

A Go-based MCP server that provides comprehensive access to the Serper Google Search API, including tools for images, news, maps, and scholar results. It also features a dedicated endpoint for scraping webpage content directly.

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.

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.

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.

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.

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.

A native, local-first, multilingual memory server for Codex, Claude Code, and any MCP client, providing hybrid semantic and exact memory recall using Go, Qdrant, and bge-m3. It enables stable, concurrent memory storage and retrieval without Docker or cloud dependencies.

🧠 High-performance persistent memory system for Model Context Protocol (MCP) powered by libSQL. Features vector search, semantic knowledge storage, and efficient relationship management - perfect for AI agents and knowledge graph applications.

Fast hybrid code search for agents. Pure Go, single static binary, BM25 lexical + Model2Vec semantic embeddings + RRF fusion + a code-aware reranker, with the retrieval algorithm ported verbatim from semble

MCP server for local-first code intelligence, providing structural code graph, semantic search, and impact analysis to AI agents.