"Information about Firecrawl" matching MCP servers:

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.

An MCP server for analyzing images using OpenRouter vision models, offering capabilities like automatic image resizing, model configuration, and handling custom queries about images.

Enables Claude to remember information about users across chats using a persistent local knowledge graph that stores entities, relationships, and observations.

An MCP-based trivia game server where AI creates rounds with two true statements and one false 'twist' about various topics, letting players guess which statement is false.

Enables Claude to remember information about users across conversations by storing and retrieving data as entities, relations, and observations in a persistent local knowledge graph.

Generates AI-powered clarifying questions for user task requests using Claude, helping gather detailed requirements about tech stack, architecture, deployment, and project scope through categorized, contextually relevant questions.

A server that enables natural-language queries about GitHub repositories and returns answers backed by live GitHub data.

Enables an AI assistant to dynamically discover and invoke MCP tools for document search, employee information lookup, and mathematical calculations, with human-in-the-loop approval for sensitive operations.

Enables agents to get fast, calibrated probabilistic answers from Jev (Typesafe AI) to yes/no, scale, or choice questions about provided material, without using a generative model.

Enables LLMs to communicate with Agent-to-Agent (A2A) protocol compliant agents, providing tools for sending messages, managing tasks, and retrieving agent information.

Provides versioned, structured memory for AI agents, allowing them to store facts, detect conflicts, and track knowledge history via a hosted SaaS platform. It enables efficient hierarchical information retrieval and semantic search while keeping token usage constant as memory scales.

Provides AI assistants with long-term semantic memory capabilities through local vector-based storage. Enables storing, recalling, and managing information across sessions with complete privacy using ChromaDB, with no data ever leaving your machine.

Gives LLMs a genuine in-game seat in Civilization V, letting them scout, settle, negotiate, fight, and manage a civilization through tool calls with the same fog-of-war information a human player sees.

Enables LLM assistants like Claude to interact with Zaif cryptocurrency exchange through natural language, supporting market information retrieval, chart data, trading, and account management for BTC/JPY, ETH/JPY, and XYM/JPY pairs.

Lets MCP clients ask typed questions — yes/no, choice, or score — about structured state, including images, and receive calibrated probabilities from System One decision models such as TypeSafe Jev and Cloudflare Clef. Supports TypeSafe, OpenRouter, and local providers selectable per request, with input validation and cost reporting.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

Lets an AI agent ask real humans a question when the web genuinely has no answer, and get verbatim replies back with a respondent count. Built for the moment an agent is about to say "you should validate this with real users". Remote MCP, plain POST, or a single GET. No signup, no API key.

Enables coding agents to request calibrated probability judgments over typed questions—yes/no, named choices, or ordered scores—about a described situation, returning one probability per option rather than free text. Runs Cloudflare's Clef model locally on Apple Silicon Macs, with images or video frames optionally attached, and answers delivered as a single MCP tool call.

Enables AI assistants to discover, retrieve details about, and manage MCP (Model Context Protocol) servers that provide additional tools and capabilities on demand.

Enables AI assistants to play Pokemon Fire Red through the mGBA emulator by providing tools for button inputs and screenshots. It allows for direct reading of real-time game state from RAM, including party information, player location, and battle status.