The hardware truth contract engine for AI engineering agents. Turns raw datasheet PDFs into verified engineering contracts across 16 extraction modules, featuring deterministic spatial document mapping, IPC-compliant PCB footprints, alternate-function matrices, and zero-hallucination mathematical audits.
List all available hardware extraction modules supported by DatasheetVend (KiCad footprints/symbols, Universal Pinout, Thermal Limits, Absolute Maximum Ratings, Timing Characteristics, Logic Levels, Register Maps, Decoupling Passive BOM, Part Number Decoders, etc.).
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| modules | Yes | |
| total_modules | Yes | Total number of available hardware extraction modules |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the agent knows this is a safe, repeatable read operation. The description adds a list of example module types, which is useful context but not additional behavioral disclosure beyond what annotations provide. It does not mention pagination, rate limits, or return format, but the output schema exists to cover that.
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 concise sentence that is front-loaded with the action and resource, followed by parenthetical examples. Every word earns its place, and there is no redundancy or filler. It is appropriately sized for the tool's simplicity.
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 listing tool with no parameters and an output schema (declared but not shown), the description covers everything an agent needs: it explains what is listed, gives examples of the content, and implies the return is a list of modules. There are no missing prerequisites or edge cases. The output schema handles return structure, so this is 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?
The tool has zero parameters, so the description does not need to compensate for missing parameter documentation. The baseline for a zero-parameter tool is 4, and the description adds no irrelevant parameter information. It correctly focuses on the tool's output rather than input.
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 'List' and the resource 'all available hardware extraction modules supported by DatasheetVend', and gives concrete examples to further clarify scope. This is specific and unambiguous, and with no sibling tools to distinguish, it fully achieves its purpose.
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 implies usage: when you need an inventory of supported hardware modules. It does not explicitly say 'use when...' or provide exclusions, but there are no alternative tools to compare against, so the context is clear enough. A minor gap is the lack of explicit guidance on when not to use it, but this is not critical for a simple listing tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
datasheetvend_list_hardware_moduleslist_hardware_modulesextract_document_mapextract_pinoutinspect_document_pagelist_hardware_modulesread_document_map_instructionsextract_document_mapextract_pinoutinspect_document_pageread_document_map_instructionsClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such as io.github.acme/server also needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.
HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at /.well-known/glama.json on the same origin as the connector, then choose Check HTTP challenge.
DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
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Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
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.
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Add one secure layer between your agents and this server.
Only one tool exists, so there is no possibility of confusing it with other tools. Its purpose is clearly stated as listing available hardware modules.
The single tool name follows a clear verb_noun convention ('list_hardware_modules'), which is consistent and predictable. There are no other names to create inconsistency.
A single tool is too few for a server that implies broad datasheet extraction capabilities. The server appears to be a thin discovery endpoint rather than a functional toolset.
The server only lists hardware extraction modules and provides no actual extraction, retrieval, or processing tools. The domain described (footprints, pinouts, thermal limits, etc.) has no usable operations, creating a severe dead end.