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AG-Bureau/mcp-search

by Various

Web search, reading, images, screenshots and multi-wave research — with per-answer confidence

MCP

AG-Bureau/mcp-search

Added 21 Sept 2026

#ai-agents #llm-tools #mcp #mcp-server #model-context-protocol #searxng #self-hosted #web-search

Overview

A Python-based Model Context Protocol server for web research. It performs web searches, reads pages, fetches images, captures screenshots, and runs multi-wave research. Each answer includes a confidence score.

Best for

Best for
Python developers building MCP-based research agents.

Use cases

  • Add web search and page reading to an MCP client
  • Run iterative multi-wave research queries
  • Collect screenshots and images as part of a research pipeline

How to use

Tools exposed

  • web_search
  • web_read
  • web_image_search
  • web_screenshot
  • web_deep_search
  • unresponsive_engines
  • engines_irrelevant
  • arguments_adjusted
  • SEARXNG_SECRET
  • LLM_API_KEY
  • LLM_API_BASE
  • LLM_MODEL_TEXT
  • LLM_MODEL_VISION
  • LLM_DISABLE_THINKING
  • READ_CONTACT
  • READ_LANGUAGES

Tested with

Continue, ChatGPT

Notes

A Python-based Model Context Protocol server for web research. It performs web searches, reads pages, fetches images, captures screenshots, and runs multi-wave research. Each answer includes a confidence score.

0 stars on GitHub. Last updated 2026-09-09. Licensed AGPL-3.0.

Use cases

  • Add web search and page reading to an MCP client
  • Run iterative multi-wave research queries
  • Collect screenshots and images as part of a research pipeline

Pros

  • Returns a confidence score with each answer
  • Covers search, reading, images, and screenshots in one tool
  • Simple Python setup for MCP environments

Cons

  • No community adoption yet (zero stars)
  • Requires an MCP client to be useful
  • Confidence scores depend on source quality

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Returns a confidence score with each answer
  • Covers search, reading, images, and screenshots in one tool
  • Simple Python setup for MCP environments

Cons

  • No community adoption yet (zero stars)
  • Requires an MCP client to be useful
  • Confidence scores depend on source quality
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