{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_9cptytqga78m","handle":"mcp-leadsclean","url":"https://wellknown.network/agents/mcp-leadsclean","links":{"self":"https://wellknown.network/agents/mcp-leadsclean/record.json","html":"https://wellknown.network/agents/mcp-leadsclean","markdown":"https://wellknown.network/agents/mcp-leadsclean/record.md","api":"https://wellknown.network/api/v1/agents/mcp-leadsclean","status":"https://wellknown.network/api/v1/agents/mcp-leadsclean/status","claim":"https://wellknown.network/agents/mcp-leadsclean/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/mcp-leadsclean/claim.json","badge":"https://wellknown.network/agents/mcp-leadsclean/badge.svg","openapi":"https://wellknown.network/openapi.json","history":"https://wellknown.network/api/v1/agents/mcp-leadsclean/history","tools":"https://wellknown.network/api/v1/agents/mcp-leadsclean/tools"},"ard":{"identifier":"urn:air::server:mcp-leadsclean","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"mcp-leadsclean","summary":"Open-source MCP Server for B2B lead intelligence extraction. Works with Claude Desktop, Cursor, and any MCP client.","description":"# LeadsClean MCP Server\n\nAn open-source MCP server that extracts structured B2B lead intelligence from company websites. Point it at any URL — get back a clean JSON object with company summary, buying signals, inferred needs, and personalised icebreaker lines.\n\nBuilt as a reference implementation for MCP tool development. Demonstrates multi-provider LLM routing, dual-transport MCP serving, GDPR compliance patterns, and API key management — patterns you can reuse in your own MCP servers.\n\nWorks with Claude Desktop, Cursor, and any MCP-compatible client.\n\n---\n\n## Tools\n\n| Tool | Description |\n|------|-------------|\n| `extract_lead_intelligence` | Analyse a single company URL and return structured lead intel |\n| `batch_extract_leads` | Analyse up to 20 URLs in parallel — designed for agent list-processing |\n\n### Output schema\n\n```json\n{\n  \"company_name\": \"Acme Hotels Group\",\n  \"core_business_summary\": \"Boutique hotel chain with 12 properties across Europe.\",\n  \"product_category_match\": \"Strong match — hotel groups purchase furniture in bulk for room refits.\",\n  \"recent_company_trigger\": \"Announced expansion to 3 new cities in Q1 2026, adding 400+ rooms.\",\n  \"inferred_business_need\": \"Bulk furnishing for new hotel rooms on tight fit-out timelines.\",\n  \"icebreaker_hook_business\": \"Running 12 properties across Europe is impressive — furnishing them at scale is where we help.\",\n  \"icebreaker_hook_news\": \"Saw the Q1 expansion news — we help hotel groups source wholesale beds and sofas fast.\",\n  \"data_provenance\": {\n    \"source_url\": \"https://acmehotels.com\",\n    \"source_type\": \"public_website\",\n    \"collection_method\": \"jina_reader_public_fetch\",\n    \"contains_pii\": false,\n    \"gdpr_basis\": \"legitimate_interest\",\n    \"gdpr_notes\": \"Extracted solely from publicly available company web pages. No personal data collected. Compliant with GDPR Art. 6(1)(f).\"\n  }\n}\n```\n\nEvery response includes `data_provenance` — a machine-readable GDPR metadata block indicating data source, PII …","publisher":null,"homepage":"https://github.com/edition/leadsclean","repository":"https://github.com/edition/leadsclean","version":"0.2.0","license":"MIT","protocols":["mcp"],"tags":["ai-agent","b2b-intelligence","claude-desktop","gdpr","lead-extraction","llm-tools","mcp","mcp-server","model-context-protocol","reference-implementation"],"pricing":null,"endpoints":[{"url":"pypi:mcp-leadsclean","type":"package_pypi","auth":null,"probeable":false}],"skills":null,"tools":null,"extra":null,"attribution":{"kind":"pypi","name":"pypi","license":"pypi","repoUrl":"pypi","summary":"pypi","version":"pypi","description":"pypi","homepageUrl":"pypi"}},"derived":{"capabilities":[{"slug":"documents.extraction","name":"Data Extraction","confidence":1,"provenance":"derived"},{"slug":"dev.docs-lookup","name":"Documentation Lookup","confidence":1,"provenance":"derived"}],"categories":["dev","documents"],"language":"en"},"observed":{"status":"unknown","statusReason":"Distributed as a package to run locally; no network endpoint to check.","lastOkAt":null,"lastProbedAt":null,"statusComputedAt":null,"reliability30d":null,"latestObservations":[],"tools":null,"package":{"name":"mcp-leadsclean","registry":"pypi","observedAt":"2026-10-28T12:22:38.940Z","publishedAt":"2026-03-03T18:16:37.745972Z","latestVersion":"0.2.0"},"toolSurface":null,"endpointFacts":[]},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"pypi","key":"mcp-leadsclean","url":"https://pypi.org/project/mcp-leadsclean/","firstSeenAt":"2026-09-10T02:23:17.782Z","fetchedAt":"2026-10-28T12:20:28.121Z","normalizedAt":"2026-10-28T12:20:28.121Z"}]},"firstSeenAt":"2026-09-10T02:23:17.782Z","updatedAt":"2026-10-28T12:22:38.940Z"}