Botverse
Server Details
Video transcoding and document conversion for AI agents. Transcode to MP4 (H.264), WebM/VP9, ProRes 422, GIF, or MP3 audio. Convert PDFs, DOCX, PPTX, XLSX, HTML, Markdown, and images. Prepaid wallet with per-job billing — no FFmpeg, no storage, no infrastructure to manage.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 4.6/5 across 9 of 9 tools scored.
Tools are mostly distinct, with clear separation between document conversion (convert_content, convert_file, convert_from_url) and video/audio transcoding (transcode_from_url, transcode_video). Support tools (get_upload_url, get_job_status, get_download_url, get_wallet_balance) are unique. Minor overlap exists between conversion variants, but descriptions effectively differentiate based on input source.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., convert_content, get_upload_url, transcode_from_url). No mixed conventions or ambiguous verbs; the naming is predictable and intuitive.
With 9 tools, the count is well-scoped for a file conversion and transcoding service. Each tool serves a distinct step in the workflow (upload, convert/transcode, status, download, balance), and there are no redundant or missing essential operations.
The tool surface covers the core workflow: upload, convert/transcode, poll status, download, and check balance. Minor gaps exist, such as the absence of job cancellation or history listing, but these are not critical for the primary use case.
Available Tools
9 toolsconvert_contentAInspect
Offload an inline document conversion to Botverse — pass the content directly as a string, get a job_id back immediately, and continue with other tasks while it converts server-side. Best choice when you already have the content in memory (e.g. Markdown you just generated or read from a file). Completes in ~2–5 seconds. Poll get_job_status while doing other work, then call get_download_url. Supported inputs: md, html, rst, txt (plain text), docx (base64). Supported outputs: docx (Word), pdf, html, txt, md, rst, xlsx. Flat fee $0.05 per file.
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | The file content as a plain text string (for md, html, rst, txt) or base64-encoded bytes (for docx). | |
| encoding | No | Encoding of the content field. Defaults to "text". Use "base64" for binary inputs like .docx. | |
| input_format | Yes | Source format of the content. | |
| output_format | Yes | Target format: docx | html | txt | md | rst | pdf | xlsx |
Output Schema
| Name | Required | Description |
|---|---|---|
| job_id | Yes | Unique identifier for this job. Pass to get_job_status and get_download_url. |
| status | Yes | Initial job state — always queued or processing immediately after submission. |
| estimated_seconds | No | Rough estimated processing time in seconds. Actual time may vary. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses async behavior (returns job_id immediately, server-side conversion), estimated time (2-5 seconds), polling needed, result retrieval via get_download_url, supported input/output formats, and flat fee. Annotations (readOnlyHint=false, destructiveHint=false) are not contradicted; description adds valuable behavioral context beyond annotations.
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?
One dense paragraph with clear front-loading of purpose and usage. Every sentence adds value: conversion description, best use case, timing, workflow, supported formats, cost. No fluff.
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?
Covers all essential aspects: what, when, how (workflow), formats, encoding, cost, timing. Output schema exists so return value details are not needed. Complete for the tool's complexity.
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?
Input schema has 100% description coverage, but description adds value by explaining how to use encoding (base64 for docx), reiterates formats, and clarifies content as string vs base64. This goes beyond the schema descriptions which are brief. Score 4 for providing extra guidance.
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?
Description clearly states the tool converts inline document content to a different format, returns a job_id, and differentiates from file-based conversion by stating it's best when content is already in memory. This distinguishes it from sibling tools like convert_file and convert_from_url.
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?
Explicitly provides when to use: when content is already in memory (e.g., Markdown just generated). Implies alternatives: for file or URL inputs use other tools. Gives workflow: poll get_job_status, then call get_download_url. Also mentions completion time and fee.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
convert_fileAInspect
Offload a document conversion to Botverse using an already-uploaded file. Workflow: (1) call get_upload_url to get a presigned upload URL, (2) PUT the raw file bytes to that URL, (3) call convert_file with the object_key — Botverse handles the rest server-side. Returns a job_id immediately so you can continue with other tasks while conversion runs. Supported inputs: md, html, rst, txt, docx. Supported outputs: docx, pdf, html, txt, md, rst, xlsx. Poll get_job_status until complete, then get_download_url. Flat fee $0.05 per file.
| Name | Required | Description | Default |
|---|---|---|---|
| object_key | Yes | The object_key returned by get_upload_url. | |
| output_format | Yes | Target format: docx | html | txt | md | rst | pdf | xlsx |
Output Schema
| Name | Required | Description |
|---|---|---|
| job_id | Yes | Unique identifier for this job. Pass to get_job_status and get_download_url. |
| status | Yes | Initial job state — always queued or processing immediately after submission. |
| estimated_seconds | No | Rough estimated processing time in seconds. Actual time may vary. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes async behavior ('returns a job_id immediately'), server-side processing, and flat fee ($0.05). Annotations already declare non-destructive and non-idempotent; the description adds valuable context about cost and polling workflow beyond what annotations provide.
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?
Single, well-structured paragraph that front-loads the purpose, lists steps, formats, and cost. Every sentence adds value, with no fluff.
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 two simple parameters, full schema descriptions, and an existing output schema (likely including job_id), the description fully covers the conversion workflow, supported formats, cost, and polling necessity. No gaps remain.
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?
Schema coverage is 100% and both parameters (object_key, output_format) are described with allowed values. The description adds that object_key comes from get_upload_url, but overall does not significantly enhance understanding beyond the schema.
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?
Clearly states the tool converts an already-uploaded file via Botverse, with specific verb ('offload a document conversion') and resource ('file'). Lists supported input and output formats, distinguishing it from siblings like convert_content or convert_from_url.
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?
Provides a clear multi-step workflow (upload first, then call convert_file, poll status, download). Implicitly differentiates from alternatives by specifying the necessary preceding steps, but does not explicitly state when to avoid this tool in favor of convert_content or convert_from_url.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
convert_from_urlAInspect
Offload a document conversion to Botverse — runs server-side in seconds, returns a download link, and frees you to continue with other tasks while it processes. Use this when the source document is at a public URL. If you already have the content as a string, use convert_content instead — no upload step needed. Supported inputs: md, html, rst, txt, docx. Supported outputs: docx (Word), pdf, html, txt, md, rst, xlsx (tables extracted). Returns a job_id immediately. Poll get_job_status every 5s until 'complete', then get_download_url. Flat fee $0.05 per file.
| Name | Required | Description | Default |
|---|---|---|---|
| source_url | Yes | Public HTTPS URL of the source document. | |
| output_format | Yes | Target format: docx | html | txt | md | rst | pdf | xlsx |
Output Schema
| Name | Required | Description |
|---|---|---|
| job_id | Yes | Unique identifier for this job. Pass to get_job_status and get_download_url. |
| status | Yes | Initial job state — always queued or processing immediately after submission. |
| estimated_seconds | No | Rough estimated processing time in seconds. Actual time may vary. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses key behavioral traits beyond annotations: asynchronous processing with immediate job_id return, polling requirements (every 5s until 'complete'), and a flat fee of $0.05 per file. No contradictions with annotations (readOnlyHint=false, destructiveHint=false, etc.).
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 concise (about 80 words) and well-structured: starts with the core function, then usage guidance, supported formats, async process, and cost. Every sentence adds value without redundancy.
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?
The description fully covers the tool's behavior: input/output highlights, async job flow with polling instructions, and cost. It integrates well with sibling tools (convert_content, get_job_status) and provides a complete usage picture.
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 description adds meaning beyond the input schema by listing supported input formats (md, html, rst, txt, docx) and explaining output formats (e.g., xlsx for table extraction). This enriches parameter understanding despite 100% 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 tool converts a document from a public URL, specifying it runs server-side and returns a download link. It explicitly distinguishes from convert_content by noting when to use each, achieving high purpose clarity.
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 explicit guidance: 'Use this when the source document is at a public URL. If you already have the content as a string, use convert_content instead.' It also details the asynchronous workflow with polling instructions, offering clear usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_download_urlARead-onlyIdempotentInspect
Get a presigned HTTPS URL to download the completed output file. Call after get_job_status returns 'complete'. URL expires in 24 hours.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes | Job ID from transcode_video, transcode_from_url, or any convert tool. |
Output Schema
| Name | Required | Description |
|---|---|---|
| filename | Yes | Suggested filename for the downloaded file including extension. |
| expires_at | Yes | ISO 8601 timestamp when the download URL expires. |
| size_bytes | No | File size of the output in bytes. |
| download_url | Yes | Presigned HTTPS GET URL for the output file. Valid for 24 hours. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate safe, idempotent, read-only behavior. Description adds the crucial expiration detail (24 hours) and the dependency on job completion, enhancing transparency without contradiction.
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?
Two sentences, no fluff, front-loaded with the key action and resource.
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 low complexity (one required parameter, simple output schema), the description fully covers purpose, usage condition, and expiration, making it complete.
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?
With 100% schema description coverage, the baseline is 3. The description adds value by specifying where the job_id comes from (output of specific tools), but this is already hinted in the schema.
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 identifies the action (get a presigned HTTPS URL), the resource (completed output file), and distinguishes it from sibling tools by specifying the prerequisite of a completed job.
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?
Explicitly states the condition for use ('Call after get_job_status returns complete'), implying when not to use, and provides context on URL expiration (24 hours).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_job_statusARead-onlyIdempotentInspect
Poll the status of a transcode or convert job. Call every 5 seconds until status is 'complete' or 'failed'. On completion your wallet is debited for the job cost.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes | Job ID returned by transcode_video, transcode_from_url, convert_file, convert_from_url, or convert_content. |
Output Schema
| Name | Required | Description |
|---|---|---|
| job_id | Yes | The job identifier. |
| status | Yes | Current job state. |
| cost_usd | No | Amount debited from the wallet on completion, in USD. |
| output_key | No | S3 object key of the completed output. Present when status is 'complete'. Pass to get_download_url. |
| progress_pct | No | Encoding progress 0–100. Only present while status is 'processing'. |
| error_message | No | Human-readable error description. Present when status is 'failed'. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds behavioral details like polling frequency and wallet debiting on completion, which are not covered by annotations. No contradiction.
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?
Three concise sentences front-load the purpose, then provide usage guidelines and a behavioral note. Every sentence adds value without redundancy.
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 tool's simplicity (1 parameter, output schema exists), the description covers all necessary aspects: purpose, polling procedure, termination conditions, and cost implications. It is complete for an agent to use correctly.
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 has 100% description coverage for the single parameter. The description adds meaning by specifying that job_id comes from specific creation tools, enhancing the schema's description.
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 tool polls the status of a transcode or convert job, which is a specific verb+resource. It distinguishes from sibling tools that initiate jobs or handle other tasks.
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 explicit guidelines: call every 5 seconds until status is 'complete' or 'failed', and use the job_id from specific creation tools. It doesn't discuss when not to use, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_upload_urlAInspect
Get a presigned PUT URL to upload any file — video, audio, or document (markdown, HTML, DOCX, etc.). The URL expires in 15 minutes. PUT raw file bytes directly to the URL. After upload, pass the object_key to transcode_video (for video) or convert_file (for documents).
| Name | Required | Description | Default |
|---|---|---|---|
| filename | Yes | Original filename including extension, e.g. report.md or footage.mp4 | |
| content_type | Yes | MIME type. Video: "video/mp4". Documents: "text/markdown", "text/html", "application/vnd.openxmlformats-officedocument.wordprocessingml.document", "text/plain". |
Output Schema
| Name | Required | Description |
|---|---|---|
| expires_in | Yes | Seconds until the upload URL expires (900 = 15 minutes). |
| object_key | Yes | S3 object key — pass this to transcode_video or convert_file. |
| upload_url | Yes | Presigned HTTPS PUT URL. Send raw file bytes as the request body. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are partially informative (readOnlyHint=false, etc.), but the description adds critical behavioral details: URL expires in 15 minutes, use PUT with raw bytes, and post-upload processing. No contradiction with annotations.
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 concise (three sentences), front-loaded with the primary action, and each sentence adds value without redundancy.
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 presence of an output schema and clear instructions, the description covers the full workflow: get URL, upload, then use other tools. It is complete for the tool's complexity.
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?
Schema coverage is 100% with good parameter descriptions. The tool description adds no additional meaning beyond the schema, so baseline score applies.
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 tool gets a presigned PUT URL for uploading any file. It specifies file types (video, audio, document) and distinguishes from siblings by noting post-upload actions (transcode_video or convert_file).
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 explains when to use the tool (to get an upload URL) and gives context about expiration and subsequent steps. However, it does not explicitly exclude cases like needing a download URL, though sibling tools imply alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_wallet_balanceARead-onlyIdempotentInspect
Check the current prepaid wallet balance for this Botverse account. Use before large batch jobs to confirm sufficient funds.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| balance_usd | Yes | Current wallet balance in USD. |
| refill_amount_usd | No | Amount in USD added on each auto-refill, if enabled. |
| auto_refill_enabled | Yes | Whether automatic wallet top-up is enabled. |
| refill_threshold_usd | No | Balance threshold in USD that triggers an auto-refill, if enabled. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description adds limited behavioral context. It mentions the check operation and prepaid nature, which is consistent but not adding critical new info.
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?
Two concise sentences, the first stating purpose and the second providing usage guidance. No wasted words.
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 tool's simplicity (no parameters, no required inputs, and an output schema exists), the description is complete and provides sufficient context for an agent.
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 input schema has zero parameters and schema description coverage is 100%. With no parameters, the baseline is 4; the description adds no parameter details, but none are needed.
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 uses a specific verb 'Check' and identifies the resource 'prepaid wallet balance for this Botverse account.' It clearly distinguishes from sibling tools which deal with conversions, uploads, and transcoding.
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 explicitly states when to use this tool: 'Use before large batch jobs to confirm sufficient funds.' It provides clear context but does not mention alternatives or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
transcode_from_urlAInspect
Offload a video or audio transcode to Botverse using a public URL — no upload step needed. Returns a job_id immediately so you can continue with other tasks while encoding runs server-side. Ideal when the source file is already hosted online (CDN, cloud storage, shared link). Limited to 2 GB. Poll get_job_status every 5 seconds until 'complete', then get_download_url. Wallet debited on completion. Use options.start_time and options.duration to trim — e.g. start_time='00:01:00', duration=120 for a 2-minute clip.
| Name | Required | Description | Default |
|---|---|---|---|
| options | No | Optional encoding parameters. All are optional. | |
| source_url | Yes | Public HTTPS URL of the source video or audio file. | |
| output_format | Yes | Target output format. One of: mp4 (H.264), webm (VP9), mov_prores (ProRes 422), mp3 (audio extraction), gif. |
Output Schema
| Name | Required | Description |
|---|---|---|
| job_id | Yes | Unique identifier for this job. Pass to get_job_status and get_download_url. |
| status | Yes | Initial job state — always queued or processing immediately after submission. |
| estimated_seconds | No | Rough estimated processing time in seconds. Actual time may vary. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint=false, etc.), the description reveals that the tool is asynchronous (returns job_id immediately), runs server-side, has a 2 GB limit, and triggers a wallet debit on completion. It also explains trimming behavior with start_time and duration. Good coverage of side effects.
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 concise and well-structured: starts with purpose, then details behavior, limits, and usage pattern. Every sentence provides essential information without redundancy.
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 tool's complexity (nested options, async behavior), the description covers key aspects: input, limitations, workflow (polling), and cost. The presence of an output schema would further reduce burden, but the description compensates well. Slight lack of return value details is mitigated by polling instructions.
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?
Schema coverage is 100%, but the description adds practical examples for start_time and duration trimming, clarifying usage. It explains optionality and provides a concrete format example. This adds value beyond the schema alone.
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?
Description clearly states the tool transcodes video/audio from a public URL without upload, and returns a job_id. It mentions use cases like CDN or cloud storage. However, it does not explicitly differentiate from sibling 'convert_from_url', which serves a similar purpose, potentially causing confusion.
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?
Provides clear guidance on when to use (source already hosted online) and includes actionable steps: poll job status every 5 seconds, then get download URL. It also notes the 2 GB limit and wallet debit. Lacks explicit 'when not to use', but the context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
transcode_videoAInspect
Offload a video transcode to Botverse — encoding runs server-side so you can continue with other tasks. Returns a job_id immediately. Source must be ≤ 10 minutes and ≤ 5 GB. Poll get_job_status every 5 seconds until 'complete', then get_download_url. Wallet debited on completion.
| Name | Required | Description | Default |
|---|---|---|---|
| options | No | Optional encoding parameters. All are optional. | |
| object_key | Yes | S3 object key returned by get_upload_url. | |
| output_format | Yes | Target output format. One of: mp4 (H.264), webm (VP9), mov_prores (ProRes 422), mp3 (audio extraction), gif. |
Output Schema
| Name | Required | Description |
|---|---|---|
| job_id | Yes | Unique identifier for this job. Pass to get_job_status and get_download_url. |
| status | Yes | Initial job state — always queued or processing immediately after submission. |
| estimated_seconds | No | Rough estimated processing time in seconds. Actual time may vary. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate mutation (readOnlyHint=false) and non-idempotent. Description adds key behaviors: wallet debited on completion, polling frequency (every 5s), source constraints. Exceeds annotation-only info.
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?
Three sentences efficiently convey purpose, constraints, and workflow. No redundant content; each sentence adds value.
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?
Completely covers purpose, constraints, workflow, and financial impact for a non-trivial tool with polling and cost. Output schema existence noted (returns job_id).
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?
All 3 parameters have comprehensive descriptions in schema (100% coverage). Description adds minor context (object_key from get_upload_url, output_format values explained) but does not significantly extend schema.
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?
Clearly states tool offloads video transcoding to server, returning job_id. Distinguishes from siblings (transcode_from_url, convert_*) by describing server-side execution and return of job_id.
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?
Provides explicit workflow: poll get_job_status, then get_download_url. Constraints on source size/duration and wallet debit provide clear when-to-use context. Does not explicitly exclude alternatives but guidance is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
Discussions
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