"SearXNG, a privacy-respecting metasearch engine" matching MCP servers:

An MCP server for connecting agentic systems to search systems via searXNG.

Exposes SearXNG web search and query autocomplete to AI clients, returning ranked results, instant answers, and suggestions with filters for category, language, time range, engines, page, and safe search. It is distributed via npx and requires a self-hosted SearXNG instance with the JSON format enabled.

Gives coding agents a single search tool backed by a self-hosted SearXNG instance, parsing and scrubbing queries, merging duplicates, and ranking results with BM25F plus optional decision-model reranking. Returns compact, token-efficient results with relevance bands, engine warnings, and optional stop/refine/broaden hints.

This server provides a privacy-focused meta search capability by integrating multiple search engines without tracking or user profiling, supporting various categories and languages for filtered searches.

Enables AI coding agents to spawn, parallelize, and synchronize multi-agent programming swarms through a stdio MCP interface. Provides tools for DAG-scheduled task dispatch, isolated Git worktree execution, atomic file locking, shared blackboard memory, and clean merging of completed agent work back to the main repository.

Wraps a dependency-free memory lifecycle engine as six read-only MCP tools, letting any agent extract facts with pure regex, score signals, compute Ebbinghaus decay and archival judgments, and simulate a full five-stage dream cycle for long-term memory growth. Runs over stdio or streamable HTTP with no API key, storing no caller data.

Enables AI coding agents to request a second opinion from a different frontier model via a single tool call, with PII scrubbed before transit, live web search, and support for Claude, ChatGPT, Cursor, and Gemini.

Enables AI agents to request an independent second opinion from a different frontier model, with PII scrubbing before transit, live web search grounding, caching, and multi-provider failover.

An AI-native product development pipeline that guides users from idea to shipping with structured research, architecture, build, validation, and traceability using 52 tools across 4 domains.

A deterministic MCP server that executes 10-step topology pipelines on Cloudflare Workers, providing structured progress snapshots and adaptive JSON templates for AI agents.

A multi-tenant memory and reasoning substrate for AI agents that provides tenant-isolated, append-only, and auditable memory with vertical business engines for procurement, sales, project management, and more, exposed via MCP and REST.

Edge-deployed predictive decision engine and circuit-breaker orchestrator for AI agents. Features low-latency telemetry, automated failover routing, and Bitcoin Lightning micro-payments.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

Enables AI agents to control a Playwright-driven browser through natural-language instructions, including page interaction and live browser task execution.

Enables MCP clients to perform speculative tree-search action prediction and prefetching using Laplace-smoothed Markov transitions, returning deterministic JSON tool results.

Lets AI agents register, post job specs to matching specialist bots, authorize PayPal escrow funds, and capture payment only for units that pass acceptance checks. Covers the full job lifecycle — bidding, hashed contracts, funding, delivery verification, payouts, dispute mediation and long-polled events.

Provides Claude Desktop with persistent memory across sessions, storing up to 10,000 memories with semantic search and automatic context bridging. Features temporal versioning and anti-degradation protocols to maintain conversation continuity.

Discover and connect your agents with other agents via A2A protocol. Share resources for free or fee.

Enables agents to accomplish multi-step work by writing a single sandboxed JavaScript program that drives shell, filesystem, HTTP, and every tool of any configured MCP server, returning only a small summary instead of raw JSON. This collapses dozens of advertised tool schemas into one tool, cutting per-request context by roughly 26× while keeping disabled upstream servers reachable.

Enables coding agents to consult other coding-agent CLIs for independent opinions on proposals, receiving per-agent responses that can be verified and recorded without sharing conversation history.

Enables Cursor to route coding tasks across cost, balanced, and intelligence tiers based on TypeSafe Jev decisions, with optional hard model switching through the Cursor SDK.

A LangGraph-powered MCP server for infrastructure orchestration with autonomous subagents.

Enables multi-agent systems to share and coordinate a common state space over MCP, detecting concurrent mutation race conditions, synchronizing state through vector clocks, and resolving conflicting decisions via consensus arbitration. Also supports deterministic policy validation and cryptographic state hashing with zero external dependencies.

Enables hierarchical coding agents to record typed decisions into a shared append-only log and have contradicting decisions refused by deterministic comparison, with conflicts escalated up the hierarchy and a report of how few reached the human.

Provides a standardized protocol for tool invocation, enabling an AI system to search the web, retrieve information, and provide relevant answers through integration with LangChain, RAG, and Ollama.

Enables any MCP client to operate DeepSeek Harness sessions, execute tasks, and manage workspaces through an MCP server running inside the dsh process.

Enables MCP clients such as Claude Desktop, Claude Code, and Cursor to discover node types, author and validate typed multi-agent workflow files, launch runs against a workspace, and retrieve run status, node outputs, and workspace change details.

An authenticated OpenAI-compatible inference gateway with an async job broker that bridges a coding agent to a ChatGPT MCP worker, enabling ChatGPT to process inference requests via a tunnel.

Enables context optimization for LLM-powered coding assistants by compressing prompts, injecting task protocols, and providing a 2nd Brain knowledge graph with tools for prompt compression, knowledge retrieval, metrics, and runtime configuration.

Enables agents to enrich domains into public business contact data, including MX/disposable-validated role emails, phones, social profiles, company names, and addresses, while respecting robots.txt; also normalizes URLs and emails into unique domains locally.