CertScore.ai
Server Details
Scan public websites for privacy, cookie, tracker, consent, policy, and disclosure risk signals. Start instantly with zero-auth Light mode—no account or API key required.
- Status
- Healthy
- 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 3 of 3 tools scored.
Each tool has a clearly distinct role in the scan lifecycle: initiating a scan, polling its status, and retrieving the complete result bundle. There is no overlap or ambiguity between them.
All tool names follow a consistent pattern: the certscore_ prefix followed by a verb_noun structure (scan_site, get_scan_status, get_scan_bundle). This makes the purpose of each tool predictable and easy to remember.
Three tools is exactly the right number for this narrow, single-workflow server. Each tool is essential and there is no bloat or redundancy.
The tool surface covers the full scan lifecycle from initiation through status polling to result retrieval, including handling of all terminal states. No obvious operations are missing for the stated purpose.
Available Tools
3 toolscertscore_get_scan_bundleGet scan bundleAInspect
Call after completed or completed_limited status. Every usable completed bundle returns a self-contained concise TextContent digest plus matching structuredContent. The default summary includes the canonical report overview, up to five compact public-safe projected findings across the scan's observed domains, and bounded row-level pre-consent cookie/tracker evidence; detail=findings increases the default finding allowance, evidence adds bounded evidence digests and references, and full adds all available bounded sections. Every response declares finding and evidence total/returned/truncated counts, byte-budget metadata, omittedSections, retrieval URLs, and nextRecommendedMaxBytes when truncated. Enumerate only returned observations and projected findings. The CertScore score covers observable scan signals only; do not infer unobserved technologies or legal compliance status, and never interpret no-go, not-observed, or limited coverage as proof of compliance.
| Name | Required | Description | Default |
|---|---|---|---|
| detail | No | Response detail. Defaults to summary; evidence and full opt into heavier retained context. | |
| scanId | Yes | Stable CertScore scan ID. | |
| maxBytes | No | Maximum serialized structured response size in bytes. Defaults to 50000. | |
| maxFindings | No | Maximum compact findings to return. Defaults to 5 for summary and 20 otherwise. | |
| maxPreConsentRows | No | Maximum compact pre-consent inventory rows to return. Defaults to 20. |
Output Schema
| Name | Required | Description |
|---|---|---|
| url | Yes | |
| noGo | No | |
| type | Yes | |
| error | Yes | |
| links | No | |
| score | Yes | |
| detail | Yes | |
| domain | Yes | |
| scanId | Yes | |
| status | Yes | |
| timing | Yes | |
| summary | Yes | |
| coverage | No | |
| findings | Yes | |
| createdAt | Yes | |
| reportUrl | Yes | |
| riskLevel | Yes | |
| startedAt | Yes | |
| disclaimer | Yes | |
| fullReport | No | |
| provenance | Yes | |
| scoreLabel | Yes | |
| completedAt | Yes | |
| mcpMetadata | Yes | |
| scoreStatus | Yes | |
| scoreVersion | Yes | |
| scoreUpdatedAt | Yes | |
| evidenceSummary | No | |
| scanTimeSeconds | Yes | |
| findingsMetadata | Yes | |
| resultDisposition | No | |
| recommendedNextTool | Yes | |
| recommendedNextAction | Yes | |
| interpretationGuidance | Yes | |
| observationOnlyDisclaimer | Yes | |
| preConsentCookiesTrackers | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description richly details response contents, byte-budget metadata, truncation behavior with nextRecommendedMaxBytes, omittedSections, and imposes important interpretation caveats. It adds substantial behavioral context beyond the sparse annotations.
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 a bit lengthy but every sentence carries useful information, starting with usage guidance and then detailing response structure and caveats. It is well-structured for the tool's complexity.
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 tool's complexity, the description covers usage preconditions, response contents, detail levels, truncation metadata, and critical interpretation guardrails. The presence of an output schema reduces the need to describe return format, and the description compensates well.
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% (parameters described), but the description adds value by explaining how detail levels (summary, findings, evidence, full) affect output, default finding allowances, and truncation behavior. It enhances understanding beyond raw schema definitions.
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 retrieves a scan bundle after scan completion, using the specific verb 'get' and resource 'scan bundle'. It distinguishes from siblings by specifying the condition 'Call after completed or completed_limited status'.
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?
It explicitly states when to call (after completed/completed_limited status) and describes how detail levels affect output, but it does not explicitly name alternative tools or exclusion conditions. Clear context for usage is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
certscore_get_scan_statusGet scan statusARead-onlyIdempotentInspect
Poll with only the stable scanId returned by certscore_scan_site. Active responses include phase, heartbeat, estimated progress, stalled state, and retry delay. Terminal responses include the CertScore score, risk, coverage, timestamps, report URL, and an explicit next action. Stop polling at any terminal status.
| Name | Required | Description | Default |
|---|---|---|---|
| scanId | Yes | Stable CertScore scan ID returned by certscore_scan_site. |
Output Schema
| Name | Required | Description |
|---|---|---|
| url | No | |
| noGo | No | |
| type | No | |
| error | Yes | |
| jobId | No | |
| links | No | |
| phase | No | |
| score | No | |
| domain | No | |
| scanId | No | |
| status | No | |
| scan_id | No | |
| stalled | No | |
| coverage | No | |
| createdAt | No | |
| reportUrl | No | |
| riskLevel | No | |
| startedAt | No | |
| provenance | Yes | |
| scoreLabel | Yes | |
| completedAt | No | |
| scoreStatus | No | |
| scoreVersion | No | |
| lastUpdatedAt | No | |
| phaseStartedAt | No | |
| scoreUpdatedAt | No | |
| lastHeartbeatAt | No | |
| progressPercent | No | |
| scanTimeSeconds | No | |
| resultDisposition | No | |
| retryAfterSeconds | No | |
| progressIsEstimate | No | |
| recommendedNextTool | Yes | |
| recommendedNextAction | Yes | |
| interpretationGuidance | Yes | |
| estimatedRemainingSeconds | No | |
| observationOnlyDisclaimer | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool read-only and idempotent, and the description adds deeper behavioral insight: it details the content of active responses (phase, heartbeat, progress, stalled state, retry delay) and terminal responses (score, risk, coverage, timestamps, report URL, next action). This goes beyond annotations and gives the agent a clear mental model of the polling lifecycle.
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 three sentences, each with a distinct purpose: state the action, enumerate response stages, and give the stopping rule. No filler or redundancy; it is front-loaded with the core instruction.
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 one-parameter schema with an output schema present, the description covers when to use (after scan_site), what to expect (active vs terminal responses), and when to stop polling. It is complete for a polling tool.
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 a clear description of scanId. The tool description reinforces that 'only' the stable scanId is needed, implying no additional polling parameters. This is a slight semantic addition, though not substantial enough to warrant a 5.
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 opens with a specific verb 'Poll' and clearly identifies the resource as scan status, sourced from certscore_scan_site. It distinguishes itself from siblings by focusing on polling and listing active vs terminal response content, which is unique to a status endpoint.
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?
It explicitly states the stable scanId returned by certscore_scan_site as the input, establishing the correct context for use. The instruction to 'Stop polling at any terminal status' provides a clear operational rule, effectively communicating when to use and when to stop.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
certscore_scan_siteScan siteAInspect
First call. Starts or reuses a public-web scan and waits up to 45 seconds by default. If status is queued, running, or finalizing, retain scanId and poll certscore_get_scan_status using only that scanId. Stop polling at completed, completed_limited, failed, expired, or rate_limited. For usable completion, call certscore_get_scan_bundle. No-go and limited coverage are observations, never proof of compliance.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Public URL or domain to scan. | |
| scanFrom | No | Optional scan execution context for newly queued scans. | |
| freshness | No | Use latest to reuse recent scans or refresh to request a new scan when eligible. | |
| maxWaitSeconds | No | Maximum time to wait before returning the still-running job. Defaults to 45 seconds; never turns an active scan into an error. | |
| waitForCompletion | No | Wait for a completed scan resource in this tool call. Defaults to true. Set false only for an explicitly asynchronous workflow. |
Output Schema
| Name | Required | Description |
|---|---|---|
| noGo | No | |
| type | Yes | |
| error | Yes | |
| jobId | No | |
| links | No | |
| score | No | |
| domain | No | |
| scanId | No | |
| status | Yes | |
| coverage | No | |
| scanFrom | No | |
| createdAt | No | |
| reportUrl | No | |
| riskLevel | No | |
| startedAt | No | |
| provenance | Yes | |
| scoreLabel | Yes | |
| completedAt | No | |
| scoreStatus | No | |
| scoreVersion | No | |
| scoreUpdatedAt | No | |
| scanTimeSeconds | No | |
| resultDisposition | No | |
| recommendedNextTool | Yes | |
| recommendedNextAction | Yes | |
| interpretationGuidance | Yes | |
| observationOnlyDisclaimer | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds substantial behavioral context beyond annotations: default wait period, retry/reuse behavior, polling state machine, terminal states, and the interpretation caution that no-go/limited are observations not proof of compliance. No contradiction with annotations.
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?
Compact paragraph front-loaded with 'First call' that conveys the essential workflow in three sentences. Every sentence adds value with no filler.
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 having an output schema, the description covers the full lifecycle (initiation, polling, terminal states, final retrieval) and provides important interpretive guidance. It is highly complete for a scan-initiating tool with rich schema.
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% for all 5 parameters, so baseline is 3. The description references maxWaitSeconds implicitly ('waits up to 45 seconds') and freshness ('reuses') but doesn't add significant parameter-level detail 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 the tool's role as the first call to start or reuse a public-web scan and wait for a result. It distinguishes itself from siblings by explicitly naming the polling and bundle retrieval tools.
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?
Provides explicit workflow instructions: when statuses are queued/running/finalizing, poll with certscore_get_scan_status; stop at terminal states; call certscore_get_scan_bundle for usable completion. This is a clear 'when to use' with direct alternatives.
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
- AlicenseAqualityAmaintenanceGTM signal intelligence suite for AI agents. Six tools: hiring signals, tech stack detection, company-to-LinkedIn resolution, ICP scoring, job board scanning, and a combined signals aggregator. Built for outbound sales workflows.117371MIT

industrylens-mcpofficial
Flicense-qualityCmaintenanceBrowse IndustryLens's published competitive-intelligence reports and head-to-head competitor comparisons from any AI agent — real, source-backed data.
Sociality MCPofficial
Alicense-qualityDmaintenanceSocial media analytics, post insights, and competitor benchmarking for AI agents.6MIT- AlicenseAqualityAmaintenanceDetects hiring intent signals by scanning job boards for specific companies. Returns structured role data for outbound sales targeting.1761MIT