authenticated-mcp-agent
Server Details
JWT-gated LLM gateway: authenticate (bcrypt/JWT), then run a LangChain-on-Vertex Gemini completion.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 3.6/5 across 1 of 1 tools scored.
With only one tool, there is no possibility of confusion. The tool's purpose is clearly described.
The single tool name 'invoke' is a verb, but it does not follow a verb_noun pattern. However, with only one tool, there is no inconsistency, and the name is clear in context.
Having just one tool for a server that handles authentication and LLM completion feels slightly thin. While it can work, a more modular design separating authentication and completion would be more appropriate.
The tool bundles authentication and completion into a single operation, lacking separate endpoints for token management, user login/logout, or other typical gateway operations. This likely leads to dead ends for agents needing finer-grained control.
Available Tools
1 toolinvokeAInspect
JWT-gated LLM gateway: authenticate (bcrypt/JWT), then run a LangChain-on-Vertex Gemini completion. Unauthenticated calls are rejected.
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | JSON request for this capability (the same body you'd send as an A2A message). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It mentions authentication (JWT/bcrypt) and rejection of unauthenticated calls, but does not disclose behavior on success, error formats, rate limits, or idempotency. Missing important traits for a tool that combines auth and external LLM API.
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 with no wasted words. Front-loaded with purpose, then technical details. Every sentence earns its place.
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?
Despite low complexity (1 param), the tool handles authentication and external LLM calls. No output schema exists; description omits return value, error scenarios, and authentication prerequisites. Leaves significant gaps for an agent to invoke 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?
Schema coverage is 100% with one parameter described as 'JSON request'. Description adds value by clarifying the format is the same body as an A2A message, giving agents a reference point 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?
Description clearly states verb (authenticate and run completion) and resource (JWT-gated LLM gateway using LangChain on Vertex Gemini). It distinguishes itself from common invoke patterns by specifying authentication and backend.
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?
Description provides context (JWT-gated, unauthenticated rejected) but no explicit when-to-use or when-not-to-use. With no sibling tools, the context is adequate but lacks guidance on prerequisites or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
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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
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Credentials required to access the server are missing or invalid
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