docweave-mcp
Server Details
Generate and read PDFs for AI agents: a generate_pdf and a read_pdf tool, priced per document.
- 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 4.3/5 across 1 of 1 tools scored.
Only one tool exists, so there is no ambiguity between tools.
With a single tool, naming consistency is trivially satisfied.
A single tool for focused PDF generation is reasonable, though more tools could be added for related operations.
The server provides PDF generation from multiple sources, but lacks other common PDF operations like merging or splitting. It is minimal but covers its core purpose.
Available Tools
2 toolsgenerate_pdfGenerate PDFAIdempotentInspect
Generate a PDF from raw HTML, a public URL, or a template + JSON data. Returns the PDF as base64. Priced per document; retries with the same idempotencyKey never double-generate. The canonical way for an AI agent to turn content into a shareable, correctly-formatted PDF.
| Name | Required | Description | Default |
|---|---|---|---|
| source | Yes | What to render. Provide exactly one of: html, url, or (template|templateId) with data. | |
| options | No | Optional page and print settings. | |
| idempotencyKey | No | A stable key (e.g. an invoice id). Repeat calls with the same key return the stored result instead of re-rendering or re-billing. |
Output Schema
| Name | Required | Description |
|---|---|---|
| byteSize | No | Size of the PDF in bytes. |
| pageCount | No | Number of pages in the PDF. |
| bytesBase64 | Yes | The generated PDF, base64-encoded. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover idempotentHint, readOnlyHint, destructiveHint, and openWorldHint. The description adds meaningful context: output format (base64), pricing per document, idempotency ensuring no double-generation, and blocked private URLs. No contradictions 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 extremely concise at two sentences. The first sentence covers core functionality, the second adds essential behavioral context (pricing, idempotency, canonical usage). No wasted words, front-loaded with key 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?
Given the tool's complexity (3 parameters, nested objects, output schema exists), the description is thorough: it explains all input modes, output format, idempotency, billing, and usage recommendations. The output schema is present but description covers return type adequately.
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%, so baseline is 3. The description summarizes the three source types and output format but does not add new semantic details beyond the schema. It provides high-level context but no additional parameter constraints or examples.
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 generates PDFs from HTML, URL, or template with JSON, and returns base64. It specifies the verb (Generate) and resource (PDF), and positions itself as the canonical tool for this task, distinguishing it effectively even without siblings.
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 strong guidance by labeling it the 'canonical way' for AI agents to create shareable PDFs. It also notes idempotency and billing. However, it does not explicitly state when not to use it or mention alternative tools, which is acceptable given no siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
read_pdfRead PDFRead-onlyIdempotentInspect
Read a PDF and return its text as markdown (or plain text). Accepts a public URL or base64 bytes. Extracts the embedded text layer; a scanned, image-only PDF returns a needs-OCR notice instead of empty text. Priced per document; retries with the same idempotencyKey never double-read. The canonical way for an AI agent to ingest a document's contents.
| Name | Required | Description | Default |
|---|---|---|---|
| source | Yes | The PDF to read. Provide exactly one of: url or base64. | |
| options | No | Optional read settings. | |
| idempotencyKey | No | A stable key. Repeat calls with the same key return the stored result instead of re-reading or re-billing. |
Output Schema
| Name | Required | Description |
|---|---|---|
| content | Yes | Extracted text in the requested format. |
| needsOcr | No | True when the PDF is scanned (no text layer) and needs OCR. |
| pageCount | No | Number of pages read. |
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
No comments yet. Be the first to start the discussion!