"Information about crawer or crawler" matching MCP servers:

Enables autonomous web browsing and extraction by canonicalizing URLs, detecting anti-crawler traps such as circular paths and infinite pagination, pruning DOM content, mapping forms, converting tables to JSON, and evaluating agent trajectories.

Enables autonomous web agents to canonicalize URLs, detect anti-crawler traps such as circular paths and infinite pagination, prune DOM tokens, auto-map forms, transform tables into JSON, and evaluate action trajectories through MCP.

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.

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

Autonomous LLM-powered web crawler with 17 browser tools and goal-driven agent. Single Rust binary with stealth browsing, provider-agnostic LLM support, and built-in MCP server.

An MCP server that answers typed noul/choice/score questions about a given state with probability distributions and confidence, for routing, escalation, and gating decisions. It runs on pluggable backends (local Needle 3 or Laya models, or any OpenAI-compatible endpoint) and logs every decision so recorded ground truth can be used to track calibration.

Judgment calls on small, fast, cheap models: yes/no, pick-one and rating questions about any text, answered YES, NO or UNSURE. Four tools (likely, classify, rate, each) for TypeSafe's Jev, open models on Ollaya, Ollama or a local NLI model.

A Model Context Protocol server that converts Markdown content into interactive mindmaps, allowing AI assistants to visualize hierarchical information through either HTML content or saved files.

Enables cleaning and sanitizing prompts through an LLM-powered tool that removes sensitive information, provides structured feedback with notes and risks, and normalizes prompt formatting. Supports configurable local or remote OpenAI-compatible APIs with automatic secret redaction.

Enables autonomous web agents to prune DOM trees, canonicalize URLs against anti-crawler traps, auto-map form input schemas, and convert HTML/Markdown tables into typed JSON records. It also scores agent execution trajectories against gold benchmarks using action-level precision, recall, and Levenshtein sequence edit distance.

Enables asynchronous two-way messaging between Codex Desktop tasks and Claude Desktop Code sessions on Windows, allowing either side to share information, questions, or updates through MCP tools.

Enables an LLM to drive a real browser by declaring one outcome at a time, while Jev chooses the element, action, and value and Playwright executes it, returning a clear status such as done, blocked, or needs confirmation. Also exposes tools to open pages, ask yes/no or multiple-choice questions about a page, read question-relevant page text, capture snapshots and screenshots, act on elements directly, and invoke a page's own WebMCP tools.

Enables agents and services to ask small decision models typed questions about text, JSON, images, or video, returning labels, scores, or yes/no answers over MCP tools or a Jev-compatible HTTP API.

Enables local MCP clients to answer questions about the current browser page by capturing DOM context, routing them to fast or deep OpenAI models via a local model router, and optionally filling forms and submitting answers.

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.

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

Lets agents submit a traveler profile, trip context, and candidate listings to receive a deterministic, evidence-backed recommendation with score breakdowns, tradeoffs, risk flags, missing information, and confidence. It handles non-sensitive decision categories only and does not search inventory, book, transact, or persist data.

A Rust-based MCP server that provides long-term memory capabilities for AI agents using keyword-based storage and retrieval. It supports isolated namespaces for different users or projects, allowing LLMs to remember and recall information across sessions.

Enables image analysis and recognition through multiple LLM vision models (Gemini, GPT-4o, Qwen-VL, Doubao) by accepting image URLs or Base64 data and returning text descriptions or answers to questions about the images.

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.

Aziel Runtime is a node-meshed MCP software orchestration suite for digital forensics, auditing, provenance, research, intelligence-support, and secure agent workflows, with a single gated execution path, compartmentalized engines, verifiable receipts, temporal integrity, and explicit capability refusal. It is not merely an API aggregator or generic tool router.

Enables AI agents to notify users via Telegram or Discord when tasks complete, then wait for and receive the user's reply as the next instruction within the same session.

Pre-flight scoring for AI agents, returns Accelerate, Fix, or Stop with EUR value range, decision confidence, and pace-layer drag.

A minimal MCP server that lets AI agents pause for a specified duration before resuming their workflow. Useful for polling patterns like waiting for PR approval or file creation.

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.