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

MCP server that audits websites for GDPR, CCPA, and ePrivacy compliance.

Enables AI agents to install GDPR-compliant cookie consent banners on websites with a single command, handling domain registration, template assignment, and script injection.

An MCP server implementation that integrates the SearXNG API for powerful web search capabilities and uses @missionsquad/puppeteer-scraper to read and process live web content.

Provides AI agents with 200 deterministic micro-services covering code auditing, 3D/robotics, media processing, cryptography, blockchain settlement, AI safety, networking, and math, with automatic x402 USDC micropayments.

Turn the AI you already use into a game studio. Describe a game and Claude or Cursor builds it as a real 3D browser game: playable immediately, hosted on its own link, shareable with anyone. No engine, no build step, no code knowledge, nothing to export. Your AI ships the whole thing: it pulls free 3D assets, rigs characters, and playtests its own build until the game works. Free to start.

Long-term persistent memory for AI agents with hybrid search (DiskANN + FTS), bi-temporal knowledge graph, and 81.1% LongMemEval accuracy.

Enables AI agents to safely operate on PostgreSQL data through typed MCP tools with per-identity RBAC, guardrails, and immutable audit logging.

MCP server giving AI agents 86 tools for browser automation via Chrome DevTools Protocol, including navigation, click/fill ladders, network inspection, per-site cracks, and optional marketplace for site-specific knowledge packs.

Graph RAG based context management engine for coding agents

Persistent memory for AI coding assistants.

Indexes your codebase so AI coding agents can search instead of re-reading files, saving up to 94% of tokens.

Enables MCP clients to perform intelligent web searches via Traylinx's Agentic Search API, returning text summaries and structured data like HTML, images, and news.

Universal HTTP 402 Micropayment Protocol & Autonomous Economic Settlement Engine for AI Agents on Base L2.

Provides programmatic access to all Scoring Engine API functionality for managing Red/White/Blue team cybersecurity competitions, including scoreboard, overview, team management, service management, injects, notifications, and admin tools.

Enables users to compute European option prices and sensitivity metrics, run Monte Carlo GBM simulations, calculate historical/parametric VaR/CVaR, evaluate bond duration and convexity, and interpolate Nelson-Siegel yield curves through MCP.

Answers why a specific number in a Chinese listed company moved — margins, cash flow, inventory, management commentary, policy impact — by reading filed reports and IR transcripts and returning figures with the document and announcement number attached. It deliberately refuses price, valuation, and recommendation queries, returning a "gone_by_design" error instead.

Runs Monte Carlo retirement projections on the hosted QuantCalc engine, returning success rates, portfolio distributions, and the assumptions behind every number.

Enables searching and retrieving content, module information, and Twig template snippets from a-blog cms via its GET API.

Provides AI assistants with real-time, structured access to 32 privacy and AI governance laws across 28 jurisdictions to prevent hallucination in compliance answers.

Enables agents to resample reasoning paths, semantically deduplicate candidate answers, and confidence-weight votes to produce a consensus result. It also exposes verification and proof-checking tools over MCP STDIO JSON-RPC.

Enables agents to run free Answer Engine Optimization and AI visibility audits for a domain across platforms such as ChatGPT, Google AI Overviews, and Perplexity, then poll status and retrieve a shareable report URL plus structured summary.

Lets an AI assistant read call and message history, send texts and picture messages, reach Phone Book contacts by name, and — once switched on — place calls run by a voice agent, all limited to the phone numbers the user ticks. Hosted remotely with OAuth sign-in, so nothing needs to be installed locally.

Enables agents to run zero-dependency statistical modeling and data analysis through MCP, including multivariate linear regression via gradient descent, anomaly detection, time-series forecasting, hypothesis testing, and PCA dimensionality reduction.

Enables analytical pricing of European options and calculation of first- and second-order Greeks including Delta, Gamma, Vega, Theta, and Rho through MCP. It also supports related quantitative finance analytics such as Monte Carlo simulations, VaR/CVaR, bond duration, and yield curve interpolation.

MCP-first A/B testing server that enables agents to manage experiments (create, update traffic splits, read results, apply winning variants) from tools like Claude Code, with self-hosted Cloudflare backend.

Enables AI agents and MCP clients to run deterministic deep research consensus arbitration by parsing queries, evaluating source authority and contradictions, and returning structured JSON dossiers and telemetry.

Enables AI agents to perform deep research across multiple sources, arbitrating consensus while evaluating source authority and detecting contradictions. It integrates via MCP with clients like Claude Desktop and Cursor to deliver deterministic, structured research dossiers.

Memory for AI agents that keeps every claim with the source it came from, the date it was asserted, and a confidence you can re-weight per source, so your agent can say where a fact came from. Updates supersede or retract instead of overwriting, so you can replay what the store believed on any past date and review contradictions as lint findings.

Connects MCP clients to a local browser-based map editor, enabling session discovery, map state inspection, item and actor queries, actor placement and movement, selection changes, deletion, and undo/redo operations. Supports STDIO, Streamable HTTP, and legacy HTTP+SSE transports through a local WebSocket bridge.

Enables natural language interaction with complex computer vision workflows such as auto-labeling, class mapping, and embedding selection through an LLM-agnostic MCP orchestration layer.