"Semantic Scholar" matching MCP servers:

A Model Context Protocol server that provides intelligent file reading and semantic search capabilities across multiple document formats with security-first access controls.

A personal file-indexing MCP server that provides semantic and keyword search over a file index, plus file content lookup and browsing. It enables agents to search and retrieve files from a user's home directory.

Enables querying and updating Markdown frontmatter metadata using DuckDB SQL, with optional semantic search capabilities for finding similar documents based on content.

Local-first RAG MCP server that indexes local documents and provides hybrid search (semantic + keyword) with file ingestion, URL fetching, and a CLI, keeping data on-device.

Stores journal entries locally with semantic search using multilingual embeddings, and optionally syncs to a Git remote.

MCP server that enables local hybrid semantic and keyword search over private PDF, DOCX, Markdown, and text documents without sending data to embedding APIs.

A generic Markdown vault MCP server with FTS5 full-text search, semantic vector search, frontmatter-aware indexing, incremental reindexing, and non-markdown attachment support that exposes search, read, write, and edit tools.

Provides intelligent file system operations with advanced features including code analysis and modification across multiple languages, version control (Git/GitHub), file compression, encryption, semantic search, batch operations, and secure shell command execution.

Enables AI agents to perform safe, semantic edits on Markdown and DOCX documents through a normalized model with staging, diff review, and stale-edit protection.

Supercharges Claude Desktop with persistent semantic memory, sandboxed file I/O, live web search, and local emotional intelligence using a local ChromaDB and Hugging Face model.

MCP server that enables semantic search over local PDF collections using local RAG, with automatic indexing of new documents.

Persistent local memory for Claude Code that indexes every session's JSONL file verbatim into SQLite + ChromaDB. Exposes 17 MCP tools for semantic recall, deterministic file replay, and fuzzy "do you remember when..." queries across your entire session history — no API calls, nothing leaves the machine.

MCP server for managing product documentation as markdown files. Supports creating, reading, updating, deleting, and searching docs with optional semantic search.

Provides a shared, persistent workspace with versioned files, semantic search, run logging, and cross-agent provenance, allowing agents to maintain context across sessions and tools.

An MCP server that acts as a knowledge engine for software projects, delivering relevant context at the start of a task and accumulating knowledge at its end through tools like start_task, context, finish_task, remember, and search, with a file-based source of truth and optional semantic retrieval via Graphiti/Neo4j.

A local-first MCP server that provides AI agents with safe codebase access through file discovery, hybrid lexical-semantic search, and project introspection. It features durable local memory and semantic indexing while keeping all data and processing entirely on your local machine.

Provides local hybrid search over files by combining semantic vector and full-text BM25 retrieval, with MCP stdio/HTTP support, OAuth 2.1 authentication, and tools for reading and converting documents to Markdown.

Enables AI assistants to search for files and content across the file system using KDE's baloosearch tool. Provides semantic search capabilities with configurable parameters like file type, directory, and result limits.

Provides AI agents with access to file metadata, vector search, and workflow metrics. It enables operations such as file metadata retrieval and semantic search over file embeddings using pgvector.

Provides intelligent retrieval capabilities for local files by scanning directories, generating vector indexes, and enabling semantic search through RAG (Retrieval Augmented Generation) with incremental indexing support.