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get_thesis_match

Identify venture capital firms aligned with your company's profile by analyzing investment thesis compatibility, scoring fit, and providing tailored approach strategies.

Instructions

Finds the 5 VCs whose investment thesis best matches your company — scores each on fit, explains why they'd be interested, and tells you how to approach them. Saves weeks of investor research.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
productDescriptionYesWhat the company does and who it serves. Infer from conversation context if the user has already described their product.
stageYesCurrent funding stage. Infer from context if mentioned.
arrRangeNoCurrent ARR range (e.g., "$0-$500K", "$500K-$2M", "$2M-$10M"). Infer or ask.
verticalNoIndustry vertical (e.g., "AI/ML", "FinTech", "HealthTech", "SaaS"). Infer from product description.

Implementation Reference

  • The tool definition (name, description, and input schema) for 'get_thesis_match' in the catalog.
      name: 'get_thesis_match',
      description: 'Finds the 5 VCs whose investment thesis best matches your company — scores each on fit, explains why they\'d be interested, and tells you how to approach them. Saves weeks of investor research.',
      annotations: READ_ONLY,
      inputSchema: {
        type: 'object',
        properties: {
          productDescription: {
            type: 'string',
            description: 'What the company does and who it serves. Infer from conversation context if the user has already described their product.',
          },
          stage: {
            type: 'string',
            enum: ['Pre-Seed', 'Seed', 'Series A', 'Series B', 'Series C+'],
            description: 'Current funding stage. Infer from context if mentioned.',
          },
          arrRange: {
            type: 'string',
            description: 'Current ARR range (e.g., "$0-$500K", "$500K-$2M", "$2M-$10M"). Infer or ask.',
          },
          vertical: {
            type: 'string',
            description: 'Industry vertical (e.g., "AI/ML", "FinTech", "HealthTech", "SaaS"). Infer from product description.',
          },
        },
        required: ['productDescription', 'stage'],
      },
    },
  • The request handler in the MCP server that receives the tool call and proxies it to the Andru backend API.
    server.setRequestHandler(
      CallToolRequestSchema,
      async (request) => {
        if (!client) {
          return {
            content: [{ type: 'text', text: JSON.stringify({ error: 'ANDRU_API_KEY not configured. Tool execution requires an API key.' }) }],
            isError: true,
          };
        }
        const { name, arguments: args } = request.params;
        try {
          return await client.callTool(name, args || {});
        } catch (error) {
          return {
            content: [{
              type: 'text',
              text: JSON.stringify({ error: error.message }),
            }],
            isError: true,
          };
        }
      }
    );
  • The client method responsible for sending the tool execution request to the Andru backend API.
     * Execute an MCP tool.
     * @param {string} name - Tool name
     * @param {object} args - Tool arguments
     * @returns {Promise<{ content: Array<{ type: string, text: string }>, isError?: boolean }>}
     */
    async callTool(name, args) {
      return this.post('/api/mcp/tools/call', { tool: name, arguments: args });
    }

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