A
licenseNot graded
qualityF
maintenanceProvides regulatory and compliance intelligence from free government sources, including rules, recalls, enforcement actions, and comment deadlines, classified by industry and severity.
MIT
regulatory-radar
Server Details
California, US, and global climate compliance scans with source-linked deadlines.
If you are the author of this connector, you can claim ownership with GitHub, an HTTP challenge, or a DNS record. Claimed connector authors can inspect health checks, view analytics, and manage their listing.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- jdhart81/viridis-agent-fleet
- GitHub Stars
- 0
- Server Listing
- viridis-agent-fleet
Available Tools
4 toolsassess_complianceCInspect
Assess a company's compliance posture against applicable regulations.
Returns compliance level, percentage, gaps, and remediation priorities.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| sector | Yes | ||
| request_id | No | ||
| disclosures | No | ||
| payment_ref | No | ||
| company_name | Yes | ||
| jurisdiction | Yes |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
C2.9/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions return values (compliance level, percentage, gaps, remediation priorities) but does not disclose side effects, authentication needs, or prerequisites like the payment_ref parameter implying a paid service. The description is too minimal for full transparency.
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 extremely concise at two sentences, with the first sentence clearly stating the purpose and the second listing the outputs. It is front-loaded and free of unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, including payment_ref and disclosures), the description is incomplete. It lacks parameter explanations, usage context, and does not clarify how inputs like sector and jurisdiction affect the assessment. The presence of an output schema is not leveraged in the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description adds no information about any of the 6 parameters, including required ones like company_name, sector, and jurisdiction. The agent must infer their meaning from names alone, which is insufficient for correct invocation.
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 purpose: assess a company's compliance posture against regulations. It specifies the resource (company's compliance posture) and the verb (assess), making it distinct from sibling tools like scan_regulations, which focus on regulations themselves.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus its siblings, such as scan_regulations or describe_agent. There are no explicit when-to-use or when-not-to-use instructions, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
describe_agentAInspect
Fleet-standard self-description: capabilities, inputs, outputs.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
A4.3/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It transparently states that the tool returns capabilities, inputs, and outputs. For a simple read-only self-description, this is adequate and does not require more behavioral disclosure.
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 a single, front-loaded sentence with no redundancy. Every word adds value, and it is efficiently structured for quick comprehension.
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?
Given zero parameters and the presence of an output schema, the description fully covers the tool's purpose. It tells the agent exactly what the tool provides, and the output schema will detail the return format.
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?
There are zero parameters, so the baseline is 4. The description does not need to add parameter-level detail, and it meaningfully explains the tool's purpose beyond the empty 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 it is a self-description tool that outputs capabilities, inputs, and outputs. It uses specific verbs and resources, and the hyphenated 'Fleet-standard' helps distinguish it from sibling tools like assess_compliance and scan_regulations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for introspection but does not explicitly state when to use this tool versus alternatives. No exclusions or when-not-to-use guidance is provided, leaving the agent to infer context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
monitor_changesBInspect
Monitor recent regulatory changes in a jurisdiction over a trailing window.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| request_id | No | ||
| since_days | No | ||
| payment_ref | No | ||
| jurisdiction | Yes |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
B3.1/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It only says 'monitor', which suggests read-only but is not explicit. No disclosure of side effects, authentication needs, rate limits, or idempotency. For a monitoring tool, agents need to know if it's safe to call repeatedly.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no fluff, but it achieves conciseness at the expense of completeness. It could be restructured to include parameter hints or usage notes without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 4 parameters, 0% parameter description coverage, no annotations, and an existing output schema, the description provides insufficient context for correct invocation. It does not explain the trailing window behavior, parameter defaults, or return value expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description only mentions 'jurisdiction'. It does not explain 'since_days' (likely the trailing window length), 'request_id', or 'payment_ref'. The description fails to add meaning beyond the parameter names.
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 monitors recent regulatory changes in a jurisdiction over a trailing window, using a specific verb and resource. It distinguishes from siblings like 'assess_compliance' (evaluation) and 'scan_regulations' (broader search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for ongoing monitoring via 'trailing window', but lacks explicit guidance on when to use this tool vs alternatives or any exclusion criteria. No context about prerequisites or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
scan_regulationsBInspect
Scan a jurisdiction (e.g. EU, US, california, or CA for Canada), optionally filtered by sector.
Returns regulations with urgency flags and effective dates. Price: $0.25
per call after 10 free calls/day. Pay at
/x402/regulatory-radar/scan_regulations with Base USDC, cash-fund payment_ref through
escrow_checkout + confirm_escrow_funding, or use /seats.ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| sector | No | ||
| request_id | No | ||
| payment_ref | No | ||
| jurisdiction | Yes |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
B3.4/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description covers pricing ($0.25/call after 10 free calls), payment method (Base USDC, payment_ref), and endpoint path. However, it does not disclose rate limits, idempotency, or authentication requirements beyond payment context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively short (two sentences plus pricing) and front-loaded with the core purpose. However, the pricing and payment details add clutter that could be moved to annotations or separate documentation, reducing overall conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description mentions return values (regulations with urgency flags and effective dates), and the output schema exists. Yet, it lacks details on parameter meanings for request_id and payment_ref, and does not reference the output schema to agents, making it moderately complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description clarifies 'jurisdiction' and 'sector' parameters by giving examples (EU, US, etc.) and mentioning optional sector filtering. However, 'request_id' and 'payment_ref' are not explained; payment_ref is only referenced in payment instructions without defining its role as a parameter.
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 'scan' and the resource 'regulations' with a specific jurisdiction, and optionally filtered by sector. It distinguishes from siblings like 'assess_compliance' and 'monitor_changes' by focusing on raw regulatory scanning.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for scanning regulations by jurisdiction and sector, but does not explicitly state when to use this tool versus alternatives or provide exclusions. The sibling tools offer different functionalities, but no direct comparison is made.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Frequently Asked Questions
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as
io.github.alice/server, link the matching GitHub user or an account that owns the GitHub organization, then choose Claim with GitHub.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon the same origin as the connector, then choose Check HTTP challenge.DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
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
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
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 Connectors
Regulatory compliance, FDA recalls, federal register, enforcement actions & comment deadlines.
Compliance lint for AI, scraping, and privacy law. Cited findings in 200 or more jurisdictions.
39,173 US interconnection applications, 1,575 county grid scores, deadlines and policy events.
Verified, tier-0 regulatory data for AI across 850+ official sources and 50+ jurisdictions.
Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceTracks AI regulations, deadlines, risk assessments, and policy updates across multiple global jurisdictions, helping users stay compliant with evolving AI laws.17MIT
- AlicenseAqualityCmaintenanceSource-verified regulatory and compliance intelligence: 10,000+ obligations across 39 pillars, each grounded in a primary legal source with a content hash. Covers the EU AI Act, GDPR, DORA, NIS2, HIPAA, Basel III and the MITRE ATT&CK/ATLAS families.251MIT
- AlicenseNot gradedqualityCmaintenanceEnables review-gated, local-first monitoring of AI legislation, regulations, litigation, sanctions, court rules, and ethics guidance by collecting and verifying leads from official sources, managing human review workflows, and generating digests and exports.MIT
Try in Browser
Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
A3.6/5.0
Disambiguation5/5
Each tool has a clearly distinct purpose: scanning regulations, monitoring changes, assessing compliance, and self-description. No overlap or ambiguity.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern in snake_case (e.g., assess_compliance, monitor_changes). No deviations.
Tool Count5/5
With 4 tools, the set is well-scoped for the server's purpose of regulatory monitoring. It covers essential functions without being over or under.
Completeness3/5
The set covers core workflow (scan, monitor, assess) but lacks tools for detailed regulation retrieval, compliance history, or alert configuration, leaving noticeable gaps.