platform
Server Details
Backend for AI-built apps: database, auth, files, email, AI, payments, deploy, realtime. 170+ tools.
- Status
- Unhealthy
- 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 4.7/5 across 1 of 1 tools scored.
Only one tool exists, so there is no ambiguity whatsoever. The tool is clearly distinct by default.
With a single tool, naming consistency is perfect; there is no pattern to break. The name 'platform_help' is clear.
A single tool for a platform server is too few. The server's scope implies multiple functionalities, but only a help/documentation tool is provided.
The tool only provides documentation. There are no tools for actual platform operations (e.g., deploying, managing databases), leaving significant functional gaps.
Available Tools
1 toolplatform_helpAInspect
Get detailed platform documentation for a specific topic. Call this before building features you haven't used before — it returns the full reference (examples, signatures, common patterns) for one topic at a time.
Topics: sw.db, sw.fs, sw.email, sw.ai, sw.env, sw.jobs, sw.queue, sw.logs, auth, payments, deploy, inspect, functions, domains, realtime, cron, billing, dev-prod, feedback, getting-started, setup, common-mistakes, architecture-patterns, troubleshooting (legacy ctx.* topic names still resolve)
Example:
{ "topic": "sw.db" }Unknown topics return the list of available topics.
| Name | Required | Description | Default |
|---|---|---|---|
| topic | Yes | One of: sw.db, sw.fs, sw.email, sw.ai, sw.env, sw.jobs, sw.queue, sw.logs, auth, payments, deploy, inspect, functions, domains, realtime, cron, billing, dev-prod, feedback, getting-started, setup, common-mistakes, architecture-patterns, troubleshooting (legacy ctx.* names also resolve) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses behavior: it returns 'full reference (examples, signatures, common patterns) for one topic at a time.' It also specifies that unknown topics return the list of available topics, and that legacy topic names resolve. No side effects or destructive actions are relevant for a read-only documentation tool.
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: first sentence states purpose, then usage guidance, then topic list (with note on legacy names), then example, then edge-case handling. No superfluous content.
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 simple tool (one param, no siblings, no output schema), the description covers purpose, usage timing, parameter details with examples, and error handling (unknown topics). It is fully 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?
Input schema has 100% coverage for the single parameter, so baseline is 3. The description adds value by listing all topic names explicitly in the text, providing an example call, and noting legacy name resolution, which goes beyond 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's purpose: 'Get detailed platform documentation for a specific topic.' It uses a specific verb ('Get') and resource ('platform documentation'), and since there are no sibling tools, differentiation is not needed. The description is precise and unambiguous.
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: 'Call this before building features you haven't used before.' It also implies usage per topic ('one topic at a time') and mentions that unknown topics return a list of available topics, helping the agent understand fallback behavior. No explicit when-not-to-use is needed due to lack of siblings.
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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