Skip to main content
Glama
BACH-AI-Tools

B2Bhint MCP Server

search_company_by_email

Find companies associated with an email address using the B2Bhint API. Input an email to retrieve matching company information and contact data.

Instructions

Search for a company by email will return a list of companies that match the selected email

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYesExample value: rsing@tesla.com
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool returns 'a list of companies that match the selected email,' which implies a read-only, non-destructive operation, but doesn't cover aspects like error handling, rate limits, authentication needs, or what happens if no matches are found. The description is minimal and lacks critical behavioral details.

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?

The description is a single, straightforward sentence: 'Search for a company by email will return a list of companies that match the selected email.' It is front-loaded with the core purpose and avoids unnecessary details. However, it could be slightly more polished (e.g., 'Searches for companies by email and returns a list of matches'), but it's efficient with zero waste.

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

Completeness3/5

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

Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is minimally adequate. It states the purpose and return type ('a list of companies'), but lacks context on usage guidelines, behavioral traits, or error handling. For a simple search tool, this might suffice, but gaps in transparency and guidelines prevent a higher score.

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?

The input schema has 100% description coverage, with the 'email' parameter documented as 'Example value: rsing@tesla.com.' The description adds no additional meaning beyond what the schema provides, such as format requirements or search logic. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't need to given the schema's completeness.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Search for a company by email will return a list of companies that match the selected email.' It specifies the verb (search), resource (company), and key parameter (email). However, it doesn't explicitly differentiate from sibling tools like 'search_company_by_name' beyond the parameter difference, which is implied but not stated.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'search_company_by_name' or 'get_company_basic_data', nor does it specify scenarios where email-based search is preferred over name-based search or direct retrieval. Usage is implied by the description but not explicitly stated.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

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

curl -X GET 'https://glama.ai/api/mcp/v1/servers/BACH-AI-Tools/bachai-b2bhint'

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