A
licenseA
qualityA
maintenanceValidate AI claims against live data: check endpoints, count competitors, and test hypotheses. Includes free and paid tools via x402.
16
MIT
Agentic Diaries Audit
Server Details
Checks what a support agent knew but did not say against its policies. Free tier, no login.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- kandikandikandi/behavioral-audit-mcp
- GitHub Stars
- 0
- Server Listing
- Behavioral Audit MCP
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
MCP client
Glama
MCP server
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.
100% free. Your data is private.
Tool Definition Quality
A4.7/5.0
Tool DescriptionsA
Average 4.7/5 across 1 of 1 tools scored.
Server CoherenceA
Disambiguation5/5
With only one tool, there is no possibility of confusion between tools. The single tool has a clear and unique purpose.
Naming Consistency5/5
There is only one tool, so naming is trivially consistent. The name 'disclosure_check' follows a clear verb_noun pattern and is descriptive.
Tool Count4/5
One tool is slightly on the low side, but it's appropriate for the focused audit purpose of checking disclosure gaps. No additional tools are needed for the server's stated function.
Completeness5/5
The single tool fully covers the server's purpose of checking disclosure gaps in support replies. There are no missing operations within this narrow domain.
Available Tools
1 tooldisclosure_checkDisclosure CheckAInspect
Check a draft support reply for disclosure gaps before sending it. Given what the customer said and the reply you are about to send, it flags any should-know policy the customer's situation made relevant that the draft failed to proactively surface (the knew-but-did-not-say gap). Returns a verdict (pass or gap); on a gap, each missed policy and the line that should have been surfaced. It detects and suggests, it does not rewrite.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| draft_reply | Yes | The reply you are about to send. | |
| customer_message | Yes | What the customer said, verbatim. |
Tool Definition Quality
A4.7/5.0
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses behavior: it flags missed policies, returns a verdict (pass/gap), detects and suggests but does not rewrite. No contradictions.
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?
The description is concise, front-loaded with purpose, and every sentence adds value. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 2 parameters and no output schema, the description explains the return value (verdict and details) adequately. It is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and description adds meaning by mapping 'customer_message' and 'draft_reply' to the task. It provides context beyond the schema.
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 verb 'check', the resource 'draft support reply', and the context 'disclosure gaps before sending'. It precisely defines the tool's role.
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 description implies usage before sending a reply, but does not explicitly state when not to use or provide alternatives. However, the context is clear enough.
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.
Discussions
No comments yet. Be the first to start the discussion!
Related MCP Servers
- AlicenseAqualityBmaintenanceInvestigate fraud directly from Claude, Cursor, or any MCP-compatible client. Analyze suspicious activity with clear, evidence-backed verdicts. Pivot from a single signup to every account sharing the same device, IP address, or email inbox. Check entities against a cross-operator abuse network, review linked accounts, and efficiently process your fraud review queue. Read-only by default, with no r10508MIT
- Alicense-qualityBmaintenanceEnables AI agents to check whether AI assistants recommend a brand and audit a site's AI-agent readiness, providing visibility scores and specific gaps.MIT
- AlicenseAqualityBmaintenanceEnables agents to validate data safety before storing, transmitting, or logging data, preventing GDPR/HIPAA/PCI-DSS violations with clear verdicts like SAFE_TO_PROCESS, REDACT_BEFORE_PASSING, DO_NOT_STORE, or ESCALATE.3313MIT
Try in Browser
Your Connectors
Sign in to create a connector for this server.