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browseai-dev

Grounded Intelligence for AI agents. MCP server with real-time web search, evidence extraction, verification, and structured citations. The research infrastructure for LangChain, CrewAI, and custom agents.

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browseai-dev

Reliable research infrastructure for AI agents. The research layer your agents are missing.

MCP server with real-time web search, evidence extraction, and structured citations. Drop into Claude Desktop, Cursor, Windsurf, LangChain, CrewAI, or any agent pipeline.

What it does

Instead of letting your AI hallucinate, browseai-dev gives it real-time access to the web with structured, cited answers:

Your question → Web search → Neural rerank → Fetch pages → Extract claims → Verify → Cited answer (streamed)

Every answer includes:

  • Claims with source URLs, verification status, and consensus level
  • Evidence-based confidence score (0-1), not LLM self-assessed, auto-calibrated from feedback
  • Source quotes verified against actual page text
  • Atomic claim decomposition — compound facts split and verified independently
  • Execution trace with timing
  • 3 depth modes"fast" (default), "thorough" (auto-retry with rephrased queries), "deep" (premium multi-step agentic research: iterative think-search-extract-evaluate cycles with gap analysis, up to 4 steps, targets 0.85 confidence — requires BAI key + sign-in, 3x quota cost, falls back to thorough when exhausted)

Premium Features (with BROWSE_API_KEY)

Users with a BrowseAI Dev API key (bai_xxx) get enhanced verification:

  • Semantic re-ranking — search results re-scored by semantic query-document relevance
  • Semantic reranking — evidence matched by meaning, not just keywords
  • Multi-provider search — parallel search across multiple sources for broader coverage
  • Multi-pass consistency — claims cross-checked across independent extraction passes
  • Deep reasoning mode — multi-step agentic research with iterative think-search-extract-evaluate cycles, gap analysis, and cross-step claim merging (up to 4 steps, 3x quota cost, 100 deep queries/day)
  • Research Sessions — persistent memory across queries

Free BAI key users get a generous daily quota (100 premium queries/day, or ~33 deep queries/day at 3x cost each). When exceeded, queries gracefully fall back to keyword verification (deep falls back to thorough). Quota resets every 24 hours.

Sign up at browseai.dev for a free API key — 100 premium queries/day with full verification pipeline.

Quick Start

npx browseai-dev setup

This auto-configures Claude Desktop. You'll need a BrowseAI Dev API key — get one free at browseai.dev/dashboard.

Manual Setup

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "browseai-dev": {
      "command": "npx",
      "args": ["-y", "browseai-dev"],
      "env": {
        "BROWSE_API_KEY": "bai_xxx"
      }
    }
  }
}

Cursor / Windsurf

Add to your MCP settings:

{
  "browseai-dev": {
    "command": "npx",
    "args": ["-y", "browseai-dev"],
    "env": {
      "BROWSE_API_KEY": "bai_xxx"
    }
  }
}

HTTP Transport

Run as an HTTP server for browser-based clients, Smithery, or any HTTP-capable agent:

# Start with HTTP transport
npx browseai-dev --http

# Or set the port via environment variable
MCP_HTTP_PORT=3100 npx browseai-dev --http

The server exposes:

  • POST /mcp — MCP Streamable HTTP endpoint
  • GET /health — Health check

Docker

docker build -t browseai-dev ./apps/mcp
docker run -p 3100:3100 -e BROWSE_API_KEY=bai_xxx browseai-dev

MCP Tools

ToolDescription
browse_searchSearch the web via multi-provider search
browse_openFetch and parse a page into clean text
browse_extractExtract structured knowledge from a page
browse_answerFull pipeline: search + extract + cite. depth: "fast", "thorough", or "deep"
browse_compareCompare raw LLM vs evidence-backed answer
browse_clarityClarity — anti-hallucination answer engine. Three modes: mode: "prompt" (enhanced prompts only), mode: "answer" (LLM answer, default), mode: "verified" (LLM + web fusion)
browse_session_createCreate a research session (persistent memory across queries)
browse_session_askResearch within a session (recalls prior knowledge, stores new claims)
browse_session_recallQuery session knowledge without new web searches
browse_session_shareShare a session publicly (returns share URL)
browse_session_knowledgeExport all claims from a session
browse_session_forkFork a shared session to continue the research
browse_feedbackSubmit accuracy feedback on a result

Note: All tools require a BrowseAI Dev API key (bai_xxx). Get a free one at browseai.dev/dashboard.

Examples

Quick lookup:

"Use browse_answer to explain what causes aurora borealis"

Higher accuracy:

"Use browse_answer with depth thorough to research quantum computing"

Deep research (multi-step, requires BAI key):

"Use browse_answer with depth deep to compare CRISPR approaches for sickle cell disease"

Deep mode runs iterative think-search-extract-evaluate cycles: gap analysis identifies missing info, follow-up queries fill the gaps, and claims/sources are merged across steps with final re-verification. Targets 0.85 confidence across up to 4 steps. Falls back to thorough without a BAI key or when quota is exhausted.

Contradiction detection:

"Use browse_answer with depth thorough to check if coffee is good for health, and show me any contradictions"

Research session:

"Create a session called quantum-research, then ask about quantum entanglement, then ask how entanglement is used in computing"

Enterprise search:

"Use browse_answer to search our Elasticsearch at https://es.company.com/kb/_search for our refund policy"

Response structure

{
  "answer": "Aurora borealis occurs when charged particles from the Sun...",
  "confidence": 0.92,
  "claims": [
    {
      "claim": "Aurora borealis is caused by solar wind particles...",
      "sources": ["https://en.wikipedia.org/wiki/Aurora"],
      "verified": true,
      "verificationScore": 0.82,
      "consensusLevel": "strong"
    }
  ],
  "sources": [
    {
      "url": "https://en.wikipedia.org/wiki/Aurora",
      "title": "Aurora - Wikipedia",
      "domain": "en.wikipedia.org",
      "quote": "An aurora is a natural light display...",
      "verified": true,
      "authority": 0.70
    }
  ],
  "contradictions": [],
  "reasoningSteps": []
}

Why browseai-dev?

FeatureRaw LLMbrowseai-dev
SourcesNoneReal URLs with quotes
CitationsHallucinatedVerified from pages
ConfidenceUnknownEvidence-based score
DepthSingle pass3 modes: fast, thorough, deep reasoning
FreshnessTraining dataReal-time web
ClaimsMixed in textStructured + linked

Reliability

All API calls include automatic retry with exponential backoff on transient failures (429 rate limits, 5xx server errors). Auth errors fail immediately — no wasted retries.

Tech Stack

  • Search: Multi-provider (parallel search across sources)
  • Parsing: @mozilla/readability + linkedom
  • AI: OpenRouter (100+ models)
  • Verification: Hybrid keyword and semantic verification
  • Protocol: Model Context Protocol (MCP)

Agent Skills

Pre-built skills that teach coding agents when to use BrowseAI Dev tools:

npx skills add BrowseAI-HQ/browseAIDev_Skills

Skills work with Claude Code, Codex CLI, Gemini CLI, Cursor, and more. View skills →

Community

License

Apache 2.0

Keywords

mcp

FAQs

Package last updated on 04 Apr 2026

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