DataForB2B
ai.dataforb2b/dataforb2b
6 toolsHTTPregistry active
Summary
This server connects Claude to DataForB2B's 800M profile and 75M company database through their MCP endpoint. You get search operations with 60+ people filters (title, company size, location, open_to_work status) and 50+ company filters (funding, industry, size), plus enrichment calls that turn LinkedIn URLs or domains into structured contact data with verified emails. It's built for agents doing prospecting, sourcing, or lead qualification where you need to resolve decision makers at a company, build dynamic ICP lists, or enrich profiles on demand. The underlying API is credit-based REST with webhook support, and this MCP wrapper exposes those same capabilities as native tools Claude can call directly.
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Public tool metadata for what this MCP can expose to an agent.
6 tools
search_natural_languageSearch people or companies using a free-form English query. The backend LLM interprets the query and builds structured filters automatically. Use this for fuzzy intent like "software engineers in Paris with 5+ years" or "AI startups in France that raised Series A". For determi...5 params
Search people or companies using a free-form English query. The backend LLM interprets the query and builds structured filters automatically. Use this for fuzzy intent like "software engineers in Paris with 5+ years" or "AI startups in France that raised Series A". For determi...
Parameters* required
categorystring"people" to search professional profiles, "company" to search organizations.one of
people · companydefault: peopleenrich_livebooleanWhen true, results are enriched live from LinkedIn (fresher, costs more credits). When false, results are served from the cached database (faster, cheaper).default: true
pageintegerPage number, 1-indexed.default: 1
page_sizeintegerNumber of results per page (max 100).default: 25
querystringNatural language search query (min 3 chars). Examples: "Software engineers in Paris with 5+ years of experience", "AI startups in France that raised Series A", "Marketing managers at companies with...
search_peopleSearch professional profiles using structured filters. Use this when you want precise, deterministic filtering on specific columns (exact country, company size range, funding stage, etc.). For free-form queries like "AI engineers in Berlin who recently raised", prefer `search_...7 params
Search professional profiles using structured filters. Use this when you want precise, deterministic filtering on specific columns (exact country, company size range, funding stage, etc.). For free-form queries like "AI engineers in Berlin who recently raised", prefer `search_...
Parameters* required
countintegerNumber of profiles to return (1-100 recommended; max 5000).default: 25
enrich_livebooleanWhen true (1.5 credits/profile), each profile is enriched live from LinkedIn so data is fresh. When false (0.75 credits/profile), data is served from the cached database — faster and cheaper.default: true
filtersobjectFilterGroup with shape {"op": "and"|"or", "conditions": [...]}. Each condition is {"column": "<name>", "type": "<operator>", "value": <value>, "value2": <optional, for between>}. Groups can be nest...
offsetintegerPagination offset (number of results to skip).default: 0
order_byvalueColumn to sort by, e.g. "follower_count", "years_of_experience".
order_directionstringSort direction.one of
asc · descdefault: descreveal_personal_emailbooleanWhen true, the actual personal_emails array is included on each result (extra credits per email revealed). When false, only the has_personal_email boolean flag is returned.default: false
search_companySearch companies using structured filters. Use this when you want precise filtering on specific columns (industry, country, employee count range, funding stage, founded year, etc.). For free-form queries like "AI startups in France that raised Series A", prefer `search_natural...6 params
Search companies using structured filters. Use this when you want precise filtering on specific columns (industry, country, employee count range, funding stage, founded year, etc.). For free-form queries like "AI startups in France that raised Series A", prefer `search_natural...
Parameters* required
countintegerNumber of companies to return (1-100 recommended; max 1000).default: 25
enrich_livebooleanWhen true (1.5 credits/company), each company is enriched live from LinkedIn so data is fresh. When false (0.75 credits/company), data is served from the cached database — faster and cheaper.default: false
filtersobjectFilterGroup with shape {"op": "and"|"or", "conditions": [...]}. Each condition is {"column": "<name>", "type": "<operator>", "value": <value>, "value2": <optional, for between>}. Groups can be nest...
offsetintegerPagination offset (number of results to skip).default: 0
order_byvalueColumn to sort by, e.g. "follower_count", "employee_count", "founded_year", "last_funding_amount_usd".
order_directionstringSort direction.one of
asc · descdefault: descenrich_profileEnrich a single professional profile with detailed profile data, work email, personal email, and/or GitHub profile. Each enrichment flag controls one data source and bills separately.5 params
Enrich a single professional profile with detailed profile data, work email, personal email, and/or GitHub profile. Each enrichment flag controls one data source and bills separately.
Parameters* required
enrich_githubbooleanFind the person's GitHub profile URL.default: false
enrich_personal_emailbooleanFind the person's personal email.default: false
enrich_profilebooleanReturn the full profile object (experience, education, skills, etc.).default: true
enrich_work_emailbooleanFind the person's professional / work email.default: false
profile_identifierstringThe profile to enrich. Accepts any of: a LinkedIn URL (e.g. "https://linkedin.com/in/john-doe"), a public_id slug (e.g. "john-doe"), or an encoded DataForB2B ID (e.g. "prof_xxx").
enrich_companyEnrich a single company with full data from public sources (description, industry, headquarters, employee count, funding, offices, etc.).1 params
Enrich a single company with full data from public sources (description, industry, headquarters, employee count, funding, offices, etc.).
Parameters* required
company_identifierstringThe company to enrich. Accepts any of: a universal_name slug (e.g. "google"), a LinkedIn company URL (e.g. "https://linkedin.com/company/google"), or an encoded DataForB2B ID (e.g. "org_xxx").
search_lookalikeFind similar people or companies using AI-powered vector similarity. Provide either `profile` (to find similar people) OR `company` (to find similar companies) — not both. Optionally narrow results with `country` or `location`.7 params
Find similar people or companies using AI-powered vector similarity. Provide either `profile` (to find similar people) OR `company` (to find similar companies) — not both. Optionally narrow results with `country` or `location`.
Parameters* required
companyvalueSeed company to find lookalikes for. Accepts a LinkedIn company URL or universal_name slug. Mutually exclusive with `profile`.
countintegerNumber of results to return.default: 25
countryvalueRestrict results to a country. ISO-2 code (e.g. "FR", "US", "GB").
enrich_livebooleanWhen true, results are enriched live from LinkedIn (fresher, costs more credits). When false, results are served from the cached database.default: true
locationvalueRestrict results to a free-text location, e.g. "Paris" or "San Francisco Bay Area".
offsetintegerPagination offset.default: 0
profilevalueSeed profile to find lookalikes for. Accepts a LinkedIn URL, public_id slug, or member_identity. Mutually exclusive with `company`.
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Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
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