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Person Social Footprint Mapper MCP Server

Person Social Footprint Mapper MCP Server

Smithery Glama score MCP Registry npm version npm downloads license mcpservers.org

An MCP server for the Mamba Labs Person Social Footprint Mapper actor on Apify. Give it a person's full name and the domain of the company they work at. Each run returns one row with that person's public GitHub, Bluesky, personal site, Substack, and X profiles, with a status and a match confidence per platform.

What's Inside

Related MCP server: social-profile

What it does

Find a person's public profiles from a name and a company domain. You get one row per person with the GitHub profile, Bluesky profile, personal website, Substack newsletter, and X profile, each with public follower counts where the platform shows them, a status (found, ambiguous, not_found, skipped, skipped_rate_limit, blocked), and a confidence from 0 to 1.

A profile is found only at 0.8 or more, which needs evidence that ties it to the company or to another profile of the same person: a link to the company domain, the company's own team page listing it, the GitHub company field or organization membership, or two profiles that link to each other. A matching name alone is never enough, and a likely match that is not certain comes back ambiguous with no handle. No email address or phone number is ever returned, LinkedIn is never opened, and Substack is never read.

All of the work runs on Apify. This package is a thin client that starts the actor run, waits for it, and hands back the dataset rows.

Quick start

You need Node.js 18 or newer and an Apify account with an API token.

Add this to your Claude Desktop config (claude_desktop_config.json), Cursor, or any MCP client:

{
  "mcpServers": {
    "mamba-person-social-footprint-mapper": {
      "command": "npx",
      "args": [
        "-y",
        "@mambalabsdev/mcp-person-social-footprint-mapper"
      ],
      "env": {
        "APIFY_TOKEN": "your-apify-token"
      }
    }
  }
}

Restart the client. The map_person_social_footprint tool appears.

Prerequisites

  • Node.js 18 or newer.

  • An Apify API token from console.apify.com/account/integrations, set as APIFY_TOKEN. The server lists its tool without a token; a call needs one.

  • Optional: GITHUB_TOKEN, your own free GitHub token, for batches larger than a few dozen persons.

  • Optional: X_BEARER_TOKEN, your own X API bearer token. Without it the X columns return skipped.

Example prompts

  • "Find Mitchell Hashimoto's public GitHub and Bluesky profiles. He founded hashicorp.com."

  • "For these five founders and their company domains, which have a personal site or a newsletter?"

  • "Does the CTO of hubspot.com have a public GitHub profile?"

Tool

map_person_social_footprint. One tool. Example arguments:

{
  "full_name": "Mitchell Hashimoto",
  "company_domain": "hashicorp.com"
}

Inputs

Every buyer facing input of the actor. Omitted inputs take the actor's own defaults. Give full_name with company_domain, or persons. The two keys are read from this server's environment, never from tool arguments.

Input

Type

Required

Description

full_name

string

no

First and last name, for example Mitchell Hashimoto.

company_domain

string

no

The company the person works at, for example hashicorp.com.

persons

array

no

Several persons, one per entry as Full Name | company.com. Up to 200 per run.

linkedin_url

string

no

A weak hint from the words in the URL. LinkedIn is never opened.

location

string

no

City or country, a small boost when a profile agrees.

platforms

array

no

Any of github, bluesky, personal_site, substack, x. Omit for all five.

suppress_profile_urls

array

no

Profile URLs never to return.

max_charge_usd

string

no

Optional cost cap for the run.

proxy_mode

string

no

auto or direct. Default auto.

Pricing

Pay per event on Apify, billed to your Apify account. Prices in USD.

Event

Free plan

Bronze

Silver

Gold

person-mapped, per person with at least one profile found

$0.005

$0.00475

$0.0045

$0.00425

apify-actor-start, per run start

$0.0002

$0.0002

$0.0002

$0.0002

A person with nothing found, and blocked and error rows, are free. Mamba Labs pays the platform costs of the run, Apify proxy traffic included.

Your keys

The actor stores no key. GITHUB_TOKEN and X_BEARER_TOKEN are optional and are your own: this server reads them from its environment and sends them in the run input of that run only. X bills each X lookup to your own X account. With no X key, X is never contacted.

Responsible use

GitHub's Acceptable Use Policies do not allow its users' information to be used for spam, unsolicited email, or selling personal information, for example to recruiters, headhunters, and job boards. You are the data controller for the rows you collect under GDPR, CCPA, and applicable privacy laws.

Full actor documentation

apify.com/mambalabs/person-social-footprint-mapper

License

MIT. See LICENSE.

Available Tools

1 tool
map_person_social_footprintMap a person's social footprintA
Read-onlyIdempotent

Find a person's public GitHub, Bluesky, personal site, Substack, and X profiles from their full name and the domain of the company they work at. Returns one row per person with each profile URL, public follower counts, and a status (found, ambiguous, not_found, skipped, skipped_rate_limit, blocked) and a match confidence per platform. A profile counts as found only at 0.8 confidence or more, which needs a link to the company, the company's own team page, or a link to another profile of the same person; a name match alone is never enough. No emails, no phone numbers, LinkedIn is never opened, Substack is never read. X is used only when X_BEARER_TOKEN is set in this server's environment. A run that does not succeed is returned as an error with its run ID. Read-only; requires an APIFY_TOKEN and is billed per person with at least one profile found.

ParametersJSON Schema
NameRequiredDescriptionDefault
personsNoSeveral persons, one per entry as Full Name | company.com. Up to 200 per run.
locationNoOptional city or country; a profile in the same place gets a small boost.
full_nameNoThe person's first and last name, for example Mitchell Hashimoto. Give this with company_domain, or use persons.
platformsNoWhich platforms to return. Omit for all five.
proxy_modeNoauto retries a company or personal site page that refuses a direct request once through the Apify proxy; direct never uses a proxy. A reliability setting; it does not change the price. Default auto.
linkedin_urlNoOptional LinkedIn profile URL, used only for the words in it as a weak hint. LinkedIn is never opened.
company_domainNoThe domain of the company the person works at, for example hashicorp.com.
max_charge_usdNoOptional. The run stops before any row that would take its charges over this amount.
suppress_profile_urlsNoProfile URLs that must never be returned, for example people who asked to be removed.

TDQS

A4.4/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Goes well beyond the annotations (which only cover read-only/idempotent/open-world): it discloses the 0.8 confidence threshold and what evidence satisfies it, the full status vocabulary, the billing model (charged per person with at least one profile found), the APIFY_TOKEN requirement, X_BEARER_TOKEN gating, and the error-with-run-ID behavior. This is unusually rich operational context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core purpose and returns, then constraints. Dense and mostly waste-free, though the long run-on second half packs several unrelated constraints (privacy exclusions, token gating, billing, error handling) into a single block.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description carries the full burden of describing returns — and it does: one row per person, per-platform profile URLs, follower counts, statuses, and match confidence. Combined with the safety, auth, billing, and failure-mode coverage, an agent has everything needed to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so every parameter already carries its own documentation and the baseline is 3. The description reinforces a few points (proxy/price independence, LinkedIn-only-as-weak-hint, platform gating by token) but adds little parameter-level detail the schema does not already contain.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (find/map) and resource (a person's public GitHub, Bluesky, personal site, Substack, X profiles) plus the inputs required. The return shape and the confidence rule are stated up front, so the agent knows exactly what this tool produces.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives concrete conditions: X is only used when X_BEARER_TOKEN is set, LinkedIn is never opened, Substack is never read, and a run that fails returns an error with a run ID. There are no sibling tools to compare against, so the lack of explicit 'use this instead of X' routing is not a real gap.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev1.0.0
    • First observedmap_person_social_footprint

TDQS

A4.3/5.0

Scored across 1 tool

Disambiguation5/5

There is only one tool, so there is no possibility of misselection or overlapping purpose. Its scope (name + company domain in, profile URLs/confidences out) is unambiguous.

Naming Consistency5/5

The single name map_person_social_footprint follows a clear snake_case verb_noun_resource pattern and is fully self-consistent. No mixed conventions exist to cause confusion.

Tool Count3/5

A single tool for a single-purpose, batch-style operation is defensible, but it is thin: there is no separate way to fetch a prior run, check quota/rate-limit state, or process people in bulk. One tool of this complexity sits at the borderline of the 3-15 range.

Completeness3/5

The core lookup is covered, but the surface has notable gaps: errors return a run ID with no tool to retrieve or re-inspect that run, there is no batch/multi-person variant, and no way to re-run or filter without re-billing. Agents can work around these by re-calling, but it is not a complete lifecycle.

Maintenance

ActivityNo data
ResponsivenessNo issues

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