outreach-prospector-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| APOLLO_API_KEY | No | Optional Apollo.io API key used in Stage 1 of the executive waterfall enrichment. | |
| SNOV_CLIENT_ID | No | Optional Snov.io client ID used for domain prospect search and email resolution. | |
| FIRECRAWL_API_KEY | No | Optional Firecrawl API key used for the first tier of clean Markdown web scraping. If not set, the server falls back to Jina Reader or direct HTML-to-Markdown. | |
| SNOV_CLIENT_SECRET | No | Optional Snov.io client secret used for domain prospect search and email resolution. |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| scrape_clean_markdownA | Firecrawl / Jina Reader clean Markdown web scraper. Renders JS-heavy career pages, Ashby/Greenhouse/Workable boards, and company sites into clean Markdown. |
| waterfall_find_decision_makerC | OpenProspector 4-stage waterfall enrichment (Apollo.io -> Snov.io Domain Search -> Web/LinkedIn Executive Name Lookup + Hunter/Snov Resolver) with strict generic alias filtering. |
| scan_live_ats_career_opsC | Multi-ATS live scanner across Greenhouse, Ashby, Lever, Workable, SmartRecruiters, Recruitee, and live ATS search discovery across OPERATIONS, MARKETING, and AI tracks. |
| validate_outreach_payloadB | Hard Pre-Send Quality Gate: checks candidate email/DM payloads for generic aliases (info@, careers@), unreplaced template braces ({first_name}), em-dashes, and headline-to-company mismatches. |
| prepare_linkedin_outreach_for_approvalC | Finds LinkedIn decision-makers at a target company and drafts approval-gated single-angle LinkedIn outreach messages (OPERATIONS, MARKETING, or AI). |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
Two overlaps are evident: scrape_clean_markdown explicitly handles ATS/career boards that scan_live_ats_career_ops also targets, and waterfall_find_decision_maker overlaps with prepare_linkedin_outreach_for_approval, which also finds LinkedIn decision-makers. Descriptions clarify intent, but an agent can still misselect when the task is discovery or scraping.
All names use snake_case, but the verb pattern is inconsistent: scrape_clean_markdown and waterfall_find_decision_maker are multi-part or noun-led rather than simple verb_noun. The names remain readable and domain-specific overall.
Five tools is well within the ideal 3-15 range and each maps to a recognizable pipeline stage: scrape, enrich, scan, validate, and prepare. No tool feels redundant enough to remove, and the set is not thin for the apparent scope.
The set covers research, decision-maker discovery, ATS scanning, validation, and LinkedIn outreach preparation, but it lacks email outreach drafting despite validating email payloads, and has no lead/contact storage or status tracking. These are notable gaps for an end-to-end prospecting workflow.