A
licenseA
qualityD
maintenanceSecurity scanning, prompt injection detection, secret leak detection, and agent permission auditing for AI agent workflows.
8
55
MIT
fde-agent
Server Details
Diagnose AI workflows for failure, security, and handoff risks — RED/AMBER/GREEN per node.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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MCP client
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MCP server
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Managed credentials
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
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Tool Definition Quality
A4.1/5.0
Tool DescriptionsA
Average 4/5 across 1 of 1 tools scored.
Server CoherenceA
Disambiguation5/5
With only one tool, there is no possibility of confusion or overlap. The tool's purpose is clearly defined and distinct.
Naming Consistency5/5
The single tool name 'diagnose_workflow' follows a clear verb_noun pattern, which is internally consistent. Since there is only one tool, there are no conflicting conventions.
Tool Count3/5
The server contains only one tool, which feels thin for a typical server. While the tool is focused and self-contained, the count is at the borderline for a well-scoped server, which usually has 3-15 tools.
Completeness5/5
The single tool appears to fully cover its stated purpose of diagnosing agentic AI workflows, including risk analysis across multiple axes and built-in sample inputs. There are no obvious missing operations within the server's narrow domain.
Available Tools
1 tooldiagnose_workflowDiagnose an AI workflow for failure / security / handoff risksAInspect
FDE Agent pre-mortem: analyze an agentic AI workflow and return per-node RED/AMBER/GREEN risk across failure, security, and handoff axes, grounded in an incident ontology. Provide a built-in sample ('legal' or 'loan') or inline Markdown/BPMN node inventory.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| bpmn | No | Inline Markdown node inventory / BPMN text to diagnose | |
| sample | No | Built-in sample workflow to diagnose |
Tool Definition Quality
A4/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the main behavior (return risk levels) and mentions grounding in an incident ontology, but it does not explicitly state read-only/no side effects or clarify behavior when both 'bpmn' and 'sample' parameters are provided. The use of 'or' hints at mutual exclusivity but isn't explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core purpose and structured output, followed by input options. Every sentence earns its place with no redundant phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema, the description explains the return format (per-node RED/AMBER/GREEN on three axes) and input options. It lacks exact output structure details, but the core information needed to invoke and interpret results is present.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with both parameters already described in the schema. The description adds the 'either/or' relationship between 'bpmn' and 'sample', which is a small but useful clarification beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: analyze an agentic AI workflow and return per-node RED/AMBER/GREEN risk across three specific axes. The verb 'analyze' and the specific risk categories make the purpose unambiguous, even without sibling tools for differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The context is clear: this is a diagnostic 'pre-mortem' tool for agentic workflows. It implies usage when you need to assess failure, security, or handoff risks. While it doesn't explicitly mention alternatives or exclusions, the lack of sibling tools makes this less critical.
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" }]
}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.
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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
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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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