"Search or general inquiry" matching MCP servers:

Local MCP server that manages a job search using Markdown files, enabling skills tracking, gap analysis, and offer pipeline management via Claude.

Enables Claude chats to communicate across machines or sessions via shared encrypted rooms, with tools to create, join, send, read, wait, search, and delete room messages.

Provides AI agents with persistent, searchable memory using semantic search, auto-linking, and categorization, with zero-config local setup or production-ready external providers.

Local-first memory engine for AI-agent teams: private/team/project ACL, associative recall, and federated sync across nodes. One SQLite file, no LLM required.

Shared memory MCP server for AI coding agents, enabling context sharing across sessions with local SQLite or cloud-based semantic search, compatible with Claude Code and Cursor.

Enables keyword search, filtering, and retrieval of Claude Code memory files, reducing context overhead by fetching only relevant memories on demand.

Memory vaults on your own machine, one per life domain, retrieved with a local BM25 index fused with vector search, where the human decides which vaults a model may answer from. Requires the Mnemosyne OS desktop app running locally; it also reports what other coding agents on the same machine are doing.

Enables semantic search over markdown files to find related notes by meaning rather than keywords, and automatically detect duplicate content before creating new notes.

Serves organizational context to MCP-capable AI agents from a local folder or GitHub repository, and lets agents propose changes that require human approval.

A general-purpose MCP server providing web search, persistent memory storage, and secure code execution capabilities. It enables AI agents to search the web, store and retrieve data, and run Python/JavaScript code in sandboxed environments.

MCP server for Yandex Wiki with full-text search. Read and write pages, comments, attachments, and dynamic tables (grids); optional server-side read-only mode for agents. Docker-ready.

A Model Context Protocol server that enables AI models to perform real-time internet and knowledge searches through Higress, enhancing model responses with up-to-date information from Google, Bing, Arxiv, and internal knowledge bases.

Enables interaction with Obsidian vaults through the official Obsidian CLI, allowing note management, search, and vault operations without plugins or API keys.

Gives any AI tool persistent, searchable memory across sessions using hybrid semantic and keyword search, running 100% locally with no API keys or cloud dependencies.

Provides a scalable knowledge graph implementation for Model Context Protocol using Elasticsearch, enabling AI models to store and query information with advanced search capabilities, memory-like behavior, and multi-zone architecture.

An MCP server that enables interaction with Markdown knowledge bases, allowing users to search and retrieve content by tags, text, URL, or date range from their local markdown files.

Persistent knowledge layer for AI agents. Structured KB with search, investigation threads, multi-session journal, and multi-agent attribution. SQLite or PostgreSQL.

A read-only MCP server that lets AI agents search and retrieve the Wheel of Heaven corpus, including source-grounded facts, interpretations, and comparative traditions, all with full epistemic metadata.

Enables AI clients like Claude, ChatGPT, and Cursor to search, read, and write back to one cross-model Markdown library of saved articles, videos, PDFs, notes, and conversations. Hosted remote server with OAuth 2.1 or Agent-key auth and read_only, edit, or full permission tiers.

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.