Schema | LeadEnrich MCP Server

LeadEnrich MCP Server

Official

Describes the environment variables required to run the server.

Name	Required	Description	Default
`PORT`	No	Server port	8300
`APOLLO_API_KEY`	No	Apollo.io API key
`HUNTER_API_KEY`	No	Hunter.io API key
`CLEARBIT_API_KEY`	No	Clearbit API key
`LEADENRICH_API_KEY`	No	Client auth key for usage metering
`LEADENRICH_FREE_TIER_LIMIT`	No	Free tier limit	50

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.

Features and capabilities supported by this server

Protocol revision2025-11-25

Capability	Details
`tools`	{ "listChanged": true }
`logging`	{}
`prompts`	{ "listChanged": false }
`resources`	{ "subscribe": false, "listChanged": false }
`extensions`	{ "io.modelcontextprotocol/ui": {} }
`experimental`	{}

Functions exposed to the LLM to take actions

Name	Description
enrich_leadA	Enrich a single lead by cascading through Apollo, Clearbit, and Hunter. Provide at least one of: email, domain, or first_name + last_name + domain. When email is provided, all providers run concurrently for speed. When only domain/name is provided, Apollo runs first to discover the email, then Clearbit + Hunter run concurrently.
find_emailA	Find someone's email address given their name and company domain. Uses Hunter email-finder first (purpose-built for this), then falls back to Apollo people-match if Hunter doesn't find it.
enrich_companyA	Enrich a company by domain. Returns firmographic data without person-level details. Best for account-level research: industry, size, revenue, description, etc.
enrich_batchA	Enrich multiple leads concurrently. Each lead cascades through all providers.
check_usageB	Check your current usage and remaining quota.
health_checkA	Check server health and which enrichment providers are configured. Returns server status, configured providers, cache stats, and connectivity info.

Interactive templates invoked by user choice

Name	Description
No prompts

Contextual data attached and managed by the client

Name	Description
`example_result`	Example enrichment result showing the merged output format.

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/carsonlabs/leadenrich-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server