Leadpipe MCP

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Works with Claude Code, Codex, VS Code, Cursor, Windsurf, Claude Desktop. Read the repository before you give any tool access to your data.

npx agentmarket install connector/enzoemir1-leadpipe-mcp

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What this server can do and what it asks for, from its tool list and install config. Checked Oct 25, 2026.

Tools

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Node.js package

Tools (10)

Read from the source code; the running server may differ. Descriptions are the server’s own words; hidden characters are shown as [U+…].

• config_scoringScoring Configuration

  View or update the global lead scoring configuration used by lead_score. Call with no fields (empty object) to fetch the current config. Pass any subset of fields to patch-update: six dimension weights (each 0–1, should sum to ~1 but not enforced), high_value_titles (string array), high_value_industries (string array), preferred_company_sizes, and custom_rules (array of {name, condition, points}). Changes apply to future lead_score calls only — previously scored leads keep their scores until re-scored.

• lead_batch_ingestBatch Ingest Leads

  Add 1 to 100 leads in a single call. Each lead uses the same schema as lead_ingest. Returns {ingested: Lead[], skipped: Array<{email, reason}>} — duplicates are skipped (not failed) so a partial batch still succeeds. Prefer this over repeated lead_ingest calls for bulk imports (CSV/webhook drops).

• lead_demo_seedSeed Demo Leads

  Populate the pipeline with a realistic demo dataset: 14 leads across 5 archetypes (hot decision-makers, warm mid-level, cold junior/small-co, raw unenriched, and disqualified). Each lead has appropriate enrichment state, scoring breakdown, and status, so every downstream tool — lead_list, lead_search, lead_score, crm_export, and the pipeline-overview resource — returns meaningful output immediately. Use this to evaluate LeadPipe via MCP Inspector without Hunter, HubSpot, or Pipedrive API keys. Safe to call multiple times; each call appends a fresh batch with new UUIDs. Returns counts by status…

• lead_enrichEnrich Lead

  Derive and attach company data to an existing lead using the email domain: company name, industry, size, country, website, estimated headcount, and common tech stack. Uses Hunter.io enrichment when HUNTER_API_KEY is set, otherwise built-in domain heuristics. Updates the lead in place and returns the enriched record, ready for lead_score. Run this before lead_score for the best qualification accuracy.

• lead_exportExport Leads

  Push leads to an external destination. target must be one of "hubspot", "pipedrive", "google_sheets", "csv", or "json". For CRM targets (hubspot, pipedrive) the respective API key env var must be set (HUBSPOT_API_KEY, PIPEDRIVE_API_KEY) — if missing, the tool returns a dry-run payload instead of erroring. Filter the export via lead_ids (explicit list) or min_score (everything above threshold). Returns {target, count, summary, errors?}.

• lead_ingestIngest Lead

  Add a single lead to the pipeline. Required: email. Optional: first_name, last_name, job_title, company_name, phone, source ("website"|"linkedin"|"referral"|"event"|"cold_outreach"|"partner"|"other"), tags (string array), custom_fields. Returns the stored lead object with a generated UUID, initial status="new", created_at, and a null score (run lead_score to populate). Throws a duplicate error if the email is already in the pipeline — use lead_search first if you need upsert behaviour.

• lead_qualifyICP Pre-Qualification (Pre-Enrichment Filter)

  Filter leads against your Ideal Customer Profile BEFORE spending enrichment credits. Uses only locally-available signals (email domain, job_title, country, industry hints, tech_stack) so nothing is charged to Hunter.io, HubSpot, Pipedrive, or any other external service. Set auto_disqualify=true to also update rejected leads to status="disqualified" with the reject reasons stored in custom_fields. If lead_ids is omitted, evaluates every lead currently in status="new". Pairs naturally with upstream platform-detection tools (e.g. Detecto's detect_platform) — run that first to populate company.tec…

• lead_scoreScore Lead

  Compute a 6-dimensional qualification score (0-100) for a lead: job_title, company_size, industry, engagement, recency, and custom_rules. Each dimension is weighted via config_scoring; the final score is their weighted average. Updates the lead status to "qualified" (≥60) or "disqualified" (<60) and stores score_breakdown alongside the total. Returns the updated lead with the breakdown. Run lead_enrich first for the most accurate industry/size signals.

• lead_searchSearch Leadsread-only

  Search and filter the lead pipeline. Optional filters: query (free-text over name/email/company), status ("new"|"qualified"|"disqualified"|"contacted"|"converted"), min_score, max_score, source, tags (array), date_from/date_to. Pagination via limit (default 50, max 200) and offset. Returns {total, leads[]}. Use this to drive exports, targeted scoring, and dashboards.

• pipeline_statsPipeline Statisticsread-only

  Portfolio-wide pipeline analytics across all leads. Returns {total_leads, leads_today, leads_this_week, leads_this_month, avg_score, qualified_rate (percent), by_status (counts per status), by_source (counts per source), score_distribution}. Takes no input — always aggregates the full dataset. Ideal for dashboards, stand-ups, and conversion-rate tracking.

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Last commit

Sep 13, 2026 (1 month ago)

Last release

Apr 25, 2026 (6 months ago)

From GitHub (fetched Oct 24, 2026).

Details

Registry name

io.github.enzoemir1/leadpipe-mcp

Version

1.4.0

Auth

No auth

Packages

npm leadpipe-mcp-server

License

MIT

Repository

github.com/enzoemir1/leadpipe-mcp

First seen

Oct 24, 2026

Last checked

Oct 25, 2026

Source

Official MCP Registrygithub-graphql