Preflight
Server Details
Check if your MCP server is ready to publish on the MCP Registry, Smithery, or npm.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- evanfollis/skillfoundry-products
- GitHub Stars
- 0
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 2.9/5 across 1 of 1 tools scored.
Since there is only one tool, there is no possibility of confusion—its purpose is clear and unique. The tool's name and description distinctly indicate its role in validating publishability.
The tool uses a clear verb_noun format ('check_publish_readiness'), and with a single tool, naming is trivially consistent. It is descriptive and follows common conventions.
With just one tool, the server feels minimal for a validation task, but the tool is focused and well-defined. However, a typical well-scoped server would have more tools to handle different aspects, so it's borderline thin.
The tool appears to cover the entire preflight validation process, including checking multiple registries and providing evidence-backed findings. No obvious gaps exist within the stated domain.
Available Tools
1 toolcheck_publish_readinessCInspect
Validate whether an MCP server is publishable on real directories (MCP Registry, Smithery, npm). Provide raw artifact contents. Returns evidence-backed findings with source-linked directory rules.
| Name | Required | Description | Default |
|---|---|---|---|
| readme | No | Raw README content | |
| manifest | No | Raw server.json content | |
| package_json | No | Raw package.json content | |
| smithery_yaml | No | Raw smithery.yaml content | |
| pyproject_toml | No | Raw pyproject.toml content | |
| target_directories | No | Directories to check against. Defaults to all applicable. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the transparency burden. It does disclose that the tool returns evidence-backed findings and references source-linked directory rules, adding some behavioral context. However, it does not explicitly state whether the operation is read-only, whether it makes network calls, or how it handles invalid inputs, leaving gaps.
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 short (three sentences) and front-loaded with the primary purpose. However, the second sentence 'Provide raw artifact contents' is redundant with the input schema and does not earn its place. The third sentence is dense and arguably jargony, though it adds some specificity about the output.
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 tool has 6 parameters, no output schema, and no annotations, placing a heavy burden on the description. The description gives a high-level summary of the return type ('evidence-backed findings') but does not explain the structure of the findings, how 'source-linked directory rules' work, or how the tool processes the multiple raw content inputs. This is insufficient for full clarity.
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 covers 100% of parameter descriptions, so the baseline is 3. The tool description adds no additional meaning beyond what the schema already provides for individual parameters, such as the meaning of 'target_directories' defaults or how the raw content fields interact.
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's function: validating publishability of an MCP server against specific directories (MCP Registry, Smithery, npm). However, the second sentence 'Provide raw artifact contents' is ambiguous—it could be read as a user instruction or as an output feature—which slightly muddies the primary 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?
No guidance is given about when to use this tool or how it compares to alternatives. The description implies it is for pre-publishing validation, but it does not state prerequisites, timing, or exclusions (e.g., when not to use it or what to do instead).
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.
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