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Cyreslab-AI

Crunchbase MCP Server

search_people

Find individuals in Crunchbase by name, job title, or company to gather professional insights and connections for research or networking purposes.

Instructions

Search for people based on various criteria

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyNoFilter by company name
limitNoMaximum number of results to return (default: 10)
queryNoSearch query (e.g., person name)
titleNoFilter by job title

Implementation Reference

  • MCP tool handler for 'search_people' in the switch statement of CallToolRequestSchema. Parses input arguments into SearchPeopleInput, calls CrunchbaseAPI.searchPeople, and returns JSON response.
    case 'search_people': {
      if (!args || typeof args !== 'object') {
        throw new McpError(ErrorCode.InvalidParams, 'Invalid parameters');
      }
      const params: SearchPeopleInput = {
        query: typeof args.query === 'string' ? args.query : undefined,
        company: typeof args.company === 'string' ? args.company : undefined,
        title: typeof args.title === 'string' ? args.title : undefined,
        limit: typeof args.limit === 'number' ? args.limit : undefined
      };
      const people = await this.crunchbaseApi.searchPeople(params);
      return {
        content: [
          {
            type: 'text',
            text: JSON.stringify(people, null, 2),
          },
        ],
      };
    }
  • src/index.ts:279-302 (registration)
    Tool registration in ListToolsRequestSchema response, defining name, description, and inputSchema matching SearchPeopleInput.
      name: 'search_people',
      description: 'Search for people based on various criteria',
      inputSchema: {
        type: 'object',
        properties: {
          query: {
            type: 'string',
            description: 'Search query (e.g., person name)',
          },
          company: {
            type: 'string',
            description: 'Filter by company name',
          },
          title: {
            type: 'string',
            description: 'Filter by job title',
          },
          limit: {
            type: 'number',
            description: 'Maximum number of results to return (default: 10)',
          },
        },
      },
    },
  • Core implementation of searchPeople in CrunchbaseAPI class. Builds Crunchbase search query for /searches/people endpoint and handles API response/error.
    async searchPeople(params: SearchPeopleInput): Promise<Person[]> {
      try {
        // Build the query string based on the provided parameters
        let query = params.query || '';
    
        if (params.company) {
          query += ` AND featured_job_organization_name:${params.company}`;
        }
    
        if (params.title) {
          query += ` AND featured_job_title:${params.title}`;
        }
    
        const response = await this.client.get<CrunchbaseApiResponse<Person[]>>('/searches/people', {
          params: {
            query,
            limit: params.limit || 10,
            order: 'rank DESC'
          }
        });
    
        return response.data.data;
      } catch (error) {
        console.error('Error searching people:', error);
        throw this.handleError(error);
      }
    }
  • TypeScript interface defining the input parameters for search_people tool.
    export interface SearchPeopleInput {
      query?: string;
      company?: string;
      title?: string;
      limit?: number;
    }
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 only states the action ('Search') without detailing traits like whether it's read-only, requires authentication, has rate limits, returns structured data, or handles errors. For a search tool with zero annotation coverage, this is a significant gap in transparency.

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, efficient sentence with no wasted words, making it appropriately concise. However, it lacks front-loading of critical details like scope or differentiation from siblings, which could improve structure. It earns a 4 for brevity but not optimal information hierarchy.

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

Completeness2/5

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

Given the tool's complexity (search with 4 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't explain return values, error handling, or behavioral constraints, leaving gaps for an AI agent. With 100% schema coverage for inputs, it partially compensates but fails to address output or usage context adequately.

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 description adds minimal meaning beyond the input schema, which has 100% coverage with clear descriptions for all 4 parameters (company, limit, query, title). It implies filtering by 'various criteria' but doesn't elaborate on syntax, combinations, or default behaviors. With high schema coverage, the baseline is 3, as the schema does the heavy lifting without extra value from the description.

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

Purpose3/5

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

The description states the tool's purpose as 'Search for people based on various criteria', which is clear but vague. It specifies the verb ('Search') and resource ('people'), but lacks specificity about what 'people' means (e.g., employees, contacts, users) and how it differs from sibling tools like search_companies. It avoids tautology but doesn't provide enough detail to distinguish it from potential alternatives.

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 mentions 'various criteria' but doesn't specify contexts, exclusions, or prerequisites. With sibling tools like search_companies available, there's no indication of when to choose search_people over them, leaving usage decisions ambiguous for an AI agent.

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

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