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Khan Academy MCP Server

Khan Academy MCP Server

by aicoder2009
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

get_transcript

Extract video transcripts from Khan Academy or YouTube videos, providing timestamped or plain text versions for educational use.

Instructions

Get the transcript of a Khan Academy video. Returns timestamped text and a full-text version. Accepts a KA video slug/URL or YouTube URL/ID.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "slug": "<slug>"
    },
    "name": "get_transcript"
  }
}

Input Schema

NameRequiredDescriptionDefault
slugYesVideo slug, KA URL, YouTube URL, or YouTube video ID (e.g., 'math/algebra/v/intro-to-algebra', 'https://www.youtube.com/watch?v=NybHckSEQBI')
languageNoLanguage code for the transcript (default: 'en')en
formatNoOutput format: 'full' (plain text), 'timestamped' (with timestamps), 'both' (default: 'full')full

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
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. While it mentions what the tool returns ('timestamped text and a full-text version'), it doesn't describe error handling, rate limits, authentication requirements, or what happens with invalid inputs. For a tool with no annotation coverage, this leaves significant behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured in two sentences: the first states the purpose and output, the second specifies the input parameters. Every sentence earns its place with no wasted words, and key information is front-loaded.

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 no annotations and no output schema, the description provides basic purpose and parameter guidance but lacks details on return values, error conditions, or operational constraints. For a tool with 3 parameters and no structured safety/behavior annotations, the description is adequate but incomplete for full contextual understanding.

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?

Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description adds minimal value beyond the schema by mentioning the parameter types in natural language ('KA video slug/URL or YouTube URL/ID') but doesn't provide additional syntax, format details, or usage examples that aren't already in the schema descriptions.

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

Purpose5/5

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

The description clearly states the specific action ('Get the transcript'), resource ('of a Khan Academy video'), and output details ('timestamped text and a full-text version'). It distinguishes this tool from siblings like get_content or get_course by focusing specifically on video transcripts rather than general content or course structures.

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

Usage Guidelines3/5

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

The description implies usage context by specifying it accepts 'KA video slug/URL or YouTube URL/ID', but it doesn't explicitly state when to use this tool versus alternatives like get_content (which might also provide transcript data) or when not to use it (e.g., for non-video content). No explicit alternatives or exclusions are mentioned.

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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