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tldv-public

tl;dv MCP for Zoom, Google Meet and MS Teams

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by tldv-public

get-transcript

Retrieve time-stamped transcripts from Zoom, Google Meet, or MS Teams meetings by providing a meeting ID. Access speaker-labeled conversation logs for review or analysis.

Instructions

Get transcript by meeting ID. The transcript is a list of messages exchanged between the participants in the meeting. It's time-stamped and contains the speaker and the message

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
meetingIdYes

Implementation Reference

  • The MCP tool handler function that fetches the meeting transcript via TldvApi and returns it as a JSON-stringified text content block.
    async ({ meetingId }) => {
      const transcript = await tldvApi.getTranscript(meetingId);
      return {
        content: [{ type: "text", text: JSON.stringify(transcript) }]
      };
    }
  • src/index.ts:70-80 (registration)
    Registration of the 'get-transcript' tool handler with the MCP server using server.tool().
    server.tool(
      tools["get-transcript"].name,
      tools["get-transcript"].description,
      tools["get-transcript"].inputSchema.shape,
      async ({ meetingId }) => {
        const transcript = await tldvApi.getTranscript(meetingId);
        return {
          content: [{ type: "text", text: JSON.stringify(transcript) }]
        };
      }
    );
  • Tool metadata including name, description, and input schema (Zod object with meetingId: string) for 'get-transcript'.
    "get-transcript": {
      name: "get-transcript",
      description: "Get transcript by meeting ID. The transcript is a list of messages exchanged between the participants in the meeting. It's time-stamped and contains the speaker and the message",
      inputSchema: z.object({ meetingId: z.string() }),
    },
  • TldvApi class method that performs the HTTP request to retrieve the transcript from the TLDV API endpoint.
    async getTranscript(meetingId: string): Promise<TldvResponse<GetTranscriptResponse>> {
      return this.request<GetTranscriptResponse>(`/meetings/${meetingId}/transcript`);
    }
  • Zod schema definition for the GetTranscriptResponse type used in the API response validation.
    export const GetTranscriptResponseSchema = z.object({
      id: z.string(),
      meetingId: z.string(),
      data: z.array(SentenceSchema),
    });
    
    export type GetTranscriptResponse = z.infer<typeof GetTranscriptResponseSchema>;
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 describes the output format (list of time-stamped messages with speaker info) but lacks critical details: it doesn't mention whether this is a read-only operation, potential errors (e.g., invalid meeting ID), authentication needs, rate limits, or data freshness. For a tool with no annotations, 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 appropriately sized with two sentences: the first states the core purpose, and the second elaborates on the transcript content. It's front-loaded with the key action ('Get transcript by meeting ID') and avoids unnecessary details. However, it could be slightly more structured by explicitly separating purpose from output details.

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 (retrieving structured data), lack of annotations, and no output schema, the description is incomplete. It covers the output format but misses behavioral aspects like error handling, permissions, and usage context. Without annotations or output schema, the description should provide more comprehensive guidance to aid the agent.

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 1 parameter with 0% description coverage, so the description must compensate. It adds meaning by explaining that 'meetingId' is used to retrieve a transcript, but it doesn't provide format examples (e.g., UUID), validation rules, or where to obtain the ID. This gives basic context but falls short of fully compensating for the schema's lack of descriptions.

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: 'Get transcript by meeting ID' specifies the verb (get) and resource (transcript). It further elaborates that the transcript contains time-stamped messages with speaker information, which helps distinguish it from sibling tools like 'get-highlights' or 'get-meeting-metadata'. However, it doesn't explicitly differentiate from 'list-meetings', which is a minor gap.

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 like 'get-highlights' or 'get-meeting-metadata'. It mentions the transcript content but doesn't specify use cases, prerequisites, or exclusions. This leaves the agent with insufficient context to choose between sibling tools effectively.

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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