Loom Transcript MCP
Provides tools for fetching transcript text and comments from public Loom video URLs.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Loom Transcript MCPget the transcript for https://www.loom.com/share/abc123xyz"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Loom Transcript MCP (Fixed)
A working Model Context Protocol (MCP) server for fetching transcripts and comments from Loom videos.
This is a fixed fork of @daanvanhulsen/loom-transcript-mcp that resolves the 400 GraphQL errors caused by recent changes to Loom's API.
What Was Fixed
The original package stopped working due to three critical bugs:
Array vs Object: The original code sent GraphQL requests as an array
[{...}]instead of a plain object{...}, which Loom's API now rejects with a 400 error.Missing Headers: Added proper browser-like headers including
AcceptandUser-Agentto pass Loom's validation.Response Parsing: Fixed response data access from
response.data[0].datatoresponse.data.datato match the correct response format.
Installation
NPX (Recommended)
{
"mcpServers": {
"loom-transcript": {
"command": "npx",
"args": ["-y", "@bstyler/loom-transcript-mcp"]
}
}
}Docker
# Build
cd C:\MCPs\loom-transcript-mcp-fixed
docker build -t loom-transcript-mcp .
# Add to Claude config
{
"mcpServers": {
"loom-transcript": {
"command": "docker",
"args": ["run", "--rm", "-i", "loom-transcript-mcp"]
}
}
}From Source
git clone https://github.com/bStyler/loom-transcript-mcp.git
cd loom-transcript-mcp
npm install
npm run build
node dist/index.jsFeatures
getLoomTranscript: Fetches the transcript text from any public Loom video URL
getLoomComments: Fetches comments from a Loom video URL
Usage
After configuring the MCP server in Claude Desktop, you can use it like this:
Can you get the transcript from this Loom video? https://www.loom.com/share/abc123Development
npm install
npm run build
npm startLicense
MIT
Credits
Original package by @daanvanhulsen
Fixed by @bStyler
Available Tools
2 toolsgetLoomCommentsC
Get comments from a Loom video URL
| Name | Required | Description | Default |
|---|---|---|---|
| videoUrl | Yes | The Loom video URL (e.g., https://www.loom.com/share/123456) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'Get comments' implies a read operation, it doesn't specify authentication requirements, rate limits, error conditions, or what format the comments are returned in. This leaves the agent with insufficient information about how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that efficiently communicates the core functionality without any wasted words. It's appropriately sized and front-loaded with the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what format the comments are returned in, whether authentication is required, or how to handle different video states. Given the lack of structured information elsewhere, the description should provide more context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the single parameter 'videoUrl' well-documented in the schema. The description doesn't add any additional semantic context beyond what the schema already provides, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get comments') and target resource ('from a Loom video URL'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from its sibling tool 'getLoomTranscript', which would be needed for a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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, nor does it mention any prerequisites or context for usage. With a sibling tool 'getLoomTranscript' available, this represents a significant gap in helping the agent choose appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
getLoomTranscriptC
Get transcript text from a Loom video URL
| Name | Required | Description | Default |
|---|---|---|---|
| videoUrl | Yes | The Loom video URL (e.g., https://www.loom.com/share/123456) |
TDQS
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 what the tool does but doesn't add context beyond that—missing details like authentication needs, rate limits, error handling, or response format. This leaves significant gaps for a tool that likely interacts with an external API.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It is appropriately sized and front-loaded, making it easy to understand at a glance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects like how the transcript is returned, potential errors, or API constraints. For a tool that likely involves external data retrieval, more context is needed to ensure proper usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the single parameter 'videoUrl' well-documented in the schema. The description adds no additional meaning beyond what the schema provides, such as examples or constraints, so it meets the baseline for high schema coverage without compensating further.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('transcript text from a Loom video URL'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from its sibling tool 'getLoomComments', which likely retrieves comments rather than transcripts, so it misses full sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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, such as the sibling 'getLoomComments'. It lacks context on prerequisites, exclusions, or scenarios where this tool is preferred, leaving usage decisions unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
2 tool updates
v1.0.5- First observed
getLoomComments - First observed
getLoomTranscript
TDQS
The two tools have clearly distinct purposes: one retrieves comments and the other retrieves transcript text from a Loom video URL. There is no overlap or ambiguity between them, as they target different data types from the same resource.
Both tools follow a consistent verb_noun pattern with 'get' as the verb and descriptive nouns ('LoomComments', 'LoomTranscript'). The naming is uniform and predictable across the tool set.
With only 2 tools, the server feels thin for a transcript-focused domain, lacking operations like search, update, delete, or other common transcript management functions. This minimal set may limit agent capabilities for comprehensive workflows.
The tool set is severely incomplete for a transcript domain, offering only retrieval functions without create, update, delete, or search capabilities. This creates significant gaps that could lead to agent failures when trying to perform full lifecycle operations.
Resources
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