DataForB2B MCP Server
OfficialServer Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| DATAFORB2B_API_KEY | Yes | Your API key for the DataForB2B API. |
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 | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| search_peopleA | Search professional profiles using structured filters. Use this for any people search: translate the user's intent (e.g. "AI engineers in Berlin who recently raised") into structured filters on specific columns (country, company size range, funding stage, etc.). The available columns and operators are documented on the Returns paginated profiles matching ALL/ANY filter conditions depending on the To find people at a SPECIFIC company you already identified (e.g. via To target people by their COMPANY's business (e.g. "founders of AI sales-agent startups"), qualify the company itself: filter |
| search_companyA | Search companies using structured filters. Use this for any company search: translate the user's intent (e.g. "AI startups in France that raised Series A") into structured filters on specific columns (industry, country, employee count range, funding stage, founded year, etc.). The available columns and operators are documented on the Returns paginated companies matching ALL/ANY filter conditions depending on the |
| search_postsA | Search social posts by keyword on LinkedIn, Twitter/X, or Reddit — or target a single post by URL. Great for intent signals: find people talking about a topic, then use Two modes:
|
| search_jobsA | Search job postings on LinkedIn or Indeed by keyword, location, and filters (employment type, remote/onsite, seniority, freshness, employer). Useful for hiring signals: which companies are recruiting for what roles, where. |
| enrich_profileA | 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. |
| enrich_companyA | Enrich a single company with full data from public sources (description, industry, headquarters, employee count, funding, offices, etc.). |
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 6 tools
Each tool targets a distinct resource type (people, companies, posts, jobs) or a distinct action (search vs. enrich). The descriptions clearly differentiate search_people from enrich_profile and search_company from enrich_company, with no overlapping purposes.
All tool names follow a consistent verb_noun pattern: search_* for discovery and enrich_* for data augmentation. This predictable structure makes it easy to infer function from the name alone.
With 6 tools, the set is well-scoped for a B2B data platform. Each tool covers a distinct data operation (search people, companies, posts, jobs; enrich profiles, companies) without redundancy or bloat.
The tool surface covers the full expected lifecycle for a B2B data provider: discovery via search across all major entity types, and enrichment for deeper data on individuals and companies. No obvious dead ends or missing critical operations like retrieving by ID or exporting results.