AI search engine and MCP server for bots and agents. One Rust binary indexes code, docs, logs, JSONL/CSV and PDFs for BM25 full-text, vector and hybrid search, code search without grep, agent memory and RAG. Elasticsearch-compatible API; Corpus Hub serves hundreds of reference memory corpora.

Enables AI coding agents to maintain lossless, queryable long-term project memory through local SQLite storage, bi-temporal history, hybrid retrieval, and Git-backed Markdown mirrors, exposed via MCP tools and resources.

Publishes a weather MCP server that layers governance onto a working baseline: JWT scope checks on tools, logging with redaction, background tasks with progress and elicitation, and search/code-mode views of the same server. It also supports an in-process proxy provider and a packaged skill for agent-side discovery.

22 web-data tools: search, Bing, images, Reddit without authors, jobs, patents, flights and YouTube.

Deterministic knowledge for AI agents: search, fetch, cite and verify a 48M-entry knowledge base.

Fast, lightweight Firecrawl/Tavily alternative in Rust. Web scraper, crawler & search API with MCP server for AI agents. Drop-in Firecrawl-compatible API (/scrape, /crawl, /search). 2.3x faster than Tavily, 1.5x faster than Firecrawl in 1K-URL benchmarks. 6 MB RAM, single binary. Self-host or use managed cloud.

The ultimate RAG for your monorepo. Query, understand, and edit multi-language codebases with the power of AI and knowledge graphs

Symbol-level code retrieval for AI agents: fetch the function you need, not the whole file. Runs locally. 96.2% fewer tokens per lookup than grep-and-read on our 15-lookup benchmark. Works with Claude Code, Cursor, Codex and any MCP client.

The SEO command for AI agents: a free Google Search Console MCP server and CLI. Reads your real Search Console, Google Analytics and Bing data for traffic drops, quick wins, content decay, cannibalization and indexing, plus DataForSEO and Ahrefs keyword r

Caura (formerly MemClaw) — governed shared memory for AI agent fleets. Multi-agent, multi-tenant, MCP-native. Trust tiers, keystone policies, audit trails, knowledge graph, self-improving retrieval. Apache 2.0.

Your First LLM-Wiki Conversation Knowledge Base

CoexistAI is a modular, developer-friendly research assistant framework . It enables you to build, search, summarize, and automate research workflows using LLMs, web search, Reddit, YouTube, and mapping tools—all with simple MCP tool calls or API calls or Python functions.

Manage your Hevy workouts, routines, folders, and exercise templates. Create and update sessions faster, organize plans, and search exercises to build workouts quickly. Stay synced with changes so your training log is always up to date.

The open SVG brand library: 7,600+ brand logos and cloud icons (AWS, Azure, GCP) as official SVG. Search, copy, ship via npm, CDN, CLI, React, Vue, Svelte, Figma, VS Code, Raycast and MCP. Free, MIT, no gatekeeping.

Persistent session memory for AI coding agents that never leaves your machine — including the on-device model that reasons over it. Restores your prior decisions, open TODOs, and changed files across sessions; adds associative recall of related past work,

Enables agents to search and look up companies in a local mirror of India's MCA master data, decode CINs offline, and validate GSTIN structure and checksums. Every field carries provenance and explicitly flags missing or stale data instead of fabricating it.

Enables AI assistants to search a catalog of framed public-domain masterworks and NASA photography, look up available sizes, frames and prices, and quote orders before tax and shipping. It can also generate a secure Stripe Checkout link so the buyer pays directly, and report order and shipping status without exposing card data.

Enables AI assistants to search a catalogue of Quasar Framework components and paste their source code directly into a project, exposing free components to anyone and paid components when an access key is supplied.

Gmail, Outlook, Hotmail, iCloud and Fastmail at once: search, read, draft, send and organise mail.

Search, inspect and compare infrastructure tools for AI agents from a checked directory.

An open-source, local-first writing workspace where you can write with Claude Code and Codex, drawing on your own sources and past work.

Fast and Accurate Code Search for Agents. Uses 99% fewer tokens than grep+read

Semantic Intelligence for Large-Scale Engineering. Context+ is an MCP server designed for developers who demand 99% accuracy. By combining RAG, Tree-sitter AST, Spectral Clustering, and Obsidian-style linking, Context+ turns a massive codebase into a searchable, hierarchical feature graph.

Open Source Implementation of Karpathy's LLM Wiki. Upload documents, connect your Claude account via MCP, and have it write your wiki !