Website traffic, human vs bot split, realtime visitors, breakdowns and site health for your DevDome sites. Hosted remote MCP server (streamable HTTP), authenticated with a DevDome API key.
Add a website to the account. Returns the tracking snippet to install; the site stays pending until verified.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | The bare domain, e.g. example.com |
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 create operation, the immediate return value (tracking snippet), and the lifecycle state (pending until verified). This is meaningful behavioral context beyond the schema, though it omits idempotency and auth details.
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 concise sentences with no wasted words. The action is front-loaded, and the key consequences—return value and pending state—are stated clearly and efficiently.
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?
For a simple one-parameter tool with no output schema, the description covers what it does, what the caller receives, and the resulting state. The only minor gap is not explicitly naming verify_site as the next step, but the pending state implies it. The definition is fully sufficient for correct invocation.
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?
The schema already provides 100% coverage for the single parameter, including a type and example ('The bare domain, e.g. example.com'). The description adds no extra semantic detail about the domain parameter, so the baseline of 3 is appropriate.
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 specific operation ('Add a website to the account') and adds distinguishing details: it returns a tracking snippet and the site stays pending until verified. This differentiates it from sibling tools like verify_site and list_sites.
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?
The description implies the use case: register a new website to obtain a tracking snippet, and the 'pending until verified' note signals that verification is a separate step. It does not explicitly name the verify_site sibling or state when not to use this tool, so it falls just short of full guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Bot traffic on a site - DevDome separates every hit into human vs bot. kind 'bots' = known-bot catalog activity; 'threats' = suspicious/behavioral detections.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| kind | No | ||
| site | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, but it only explains that DevDome classifies hits as human vs bot and gives meaning to the two 'kind' values. It does not disclose whether the operation is read-only, how data is aggregated, response format, or potential edge cases, leaving significant behavior uncovered.
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 compact and readable, packing the key enum semantics into two sentences. The opening phrase is a bit label-like rather than a clear action statement, but there is no wasted wording.
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?
For a 3-parameter tool with no output schema or annotations, the description leaves out critical practical details: which parameters are optional, what 'days' defaults to, what the return payload looks like, and whether specific site setup is required. Agents are likely to have to inspect other signals or make assumptions to call this 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 description coverage is 0%, so the description must compensate. It does add value by explaining the 'bots' and 'threats' enum values, but it says nothing about the 'days' parameter's units/defaults or the expected format of 'site'. The partial explanation is helpful but incomplete.
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 points to bot traffic reporting for a site and defines the two subtypes ('bots' and 'threats'), which helps distinguish this tool from siblings like get_visitors or get_stats. However, it never explicitly says 'returns a report' or lists the metrics provided, leaving mild ambiguity about the exact output nature.
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?
There is no guidance about when to choose this tool over the listed siblings such as get_breakdown, get_timeseries, or get_realtime. No context is given for use cases, prerequisites, or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Top-N breakdown of a site's traffic by one dimension.
| Name | Required | Description | Default |
|---|---|---|---|
| to | No | ||
| days | No | ||
| from | No | ||
| site | Yes | ||
| limit | No | ||
| dimension | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. 'Top-N' hints at sorted output with a limit, but the description does not disclose date-range behavior, parameter interactions, result shape, or whether the operation is read-only, leaving significant ambiguity for an agent.
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 single concise sentence, front-loaded with the key output ('Top-N breakdown'). It wastes no words and is easy to scan, though it achieves conciseness at the cost of missing important behavioral and parameter context.
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?
The tool has six parameters, no output schema, and zero schema descriptions, yet the description only covers the high-level purpose. An agent cannot confidently construct a full query because date parameters are unexplained and the return structure is not described, making the description incomplete for correct invocation.
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 description coverage is 0%, so the description must compensate. It loosely maps 'site' and 'dimension' and implies 'limit' through 'Top-N', but it says nothing about 'from', 'to', or 'days', which are core to querying traffic data and are left entirely undocumented.
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 states a clear action—'Top-N breakdown'—and identifies the resource ('site's traffic') and grouping ('by one dimension'). It is specific enough to convey the core function, though it does not explicitly differentiate from siblings like get_stats or get_timeseries beyond the word 'breakdown'.
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?
There is no guidance on when to use this tool versus alternatives such as get_timeseries, get_stats, or get_visitors. The description implies a use case by its name and noun-phrase form, but it never states conditions, exclusions, or preferred alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Visitors active on the site in the last 5 minutes, with their current page and path.
| Name | Required | Description | Default |
|---|---|---|---|
| site | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden for behavioral disclosure, but it only describes the returned data (active visitors, current page/path). It does not mention whether visitors are unique, pagination, authentication requirements, or any rate limits, leaving the agent to guess about side effects and constraints.
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?
A single efficient sentence with no filler; every word contributes to the core meaning. The key qualifier 'last 5 minutes' is placed near the start.
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?
For a one-parameter tool, the description covers the basic purpose and returned fields, but the undocumented 'site' parameter and lack of any output structure leave gaps. The absence of annotations also means nothing discloses read-only behavior, though the name 'get_realtime' implies it.
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?
The schema provides only a required string named 'site' with 0% description coverage, so the description must explain how to populate it. The phrase 'on the site' weakly suggests that the parameter refers to the site identifier, but it does not specify format, accepted values, or how it maps to a site ID/domain.
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 identifies the resource (visitors active on the site) and a specific time window (last 5 minutes), which distinguishes it from the broader get_visitors sibling. It lacks an explicit verb like 'Returns' or 'Gets,' but the meaning is clear.
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?
No guidance is given on when to choose this tool over get_visitors, get_stats, or get_timeseries. The 'last 5 minutes' qualifier implies a real-time use case, but no alternatives, exclusions, or prerequisites are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Uptime/health summary for a site: status, response time, TLS/domain checks, open incidents.
| Name | Required | Description | Default |
|---|---|---|---|
| site | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of explaining behavior. It conveys that the tool performs checks and returns a summary, suggesting a read-only operation. It does not disclose auth requirements, rate limits, or what 'open incidents' means, but the stated output fields provide reasonable transparency for a simple health tool.
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 single front-loaded sentence with a compact, useful list of returned information. Every word adds value and there is no filler or repetition.
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?
For a simple one-parameter read tool, the description covers the core purpose and main output categories. It is not fully complete because it lacks parameter format guidance and does not clarify how this tool relates to verify_site or other health-adjacent tools, but the overall complexity is low.
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?
The schema only defines a required string named 'site' with no description, and schema description coverage is 0%. The description says the summary is 'for a site,' but does not specify whether the value should be a domain, URL, or site ID, leaving an important ambiguity.
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 provides an uptime/health summary for a site, listing specific contents like status, response time, TLS/domain checks, and open incidents. This distinguishes it from reporting tools like get_stats or get_realtime, though it does not explicitly name any sibling alternative.
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?
Usage is implied: when you need a site's uptime/health summary, this is the tool. However, there is no explicit guidance about when to choose this over related tools such as verify_site or get_breakdown, and no exclusionary conditions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Headline KPIs for a site: visits, visitors, pageviews, outbound clicks, bots, CTR, bounce rate, session duration. Defaults to the full retained history.
| Name | Required | Description | Default |
|---|---|---|---|
| to | No | YYYY-MM-DD | |
| days | No | Window in days (omit for full history) | |
| from | No | YYYY-MM-DD | |
| site | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It does state what metrics are returned and that the default scope is full retained history, which adds meaningful context. However, it does not indicate that this is a read-only operation, how date parameters interact, or any limitations on data retention or response size, leaving a partially opaque behavioral picture.
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 single sentence that front-loads the list of KPIs and then states the default behavior. There is no filler, and every clause provides information an agent needs.
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?
For a 4-parameter tool with no output schema and no annotations, the description is minimally adequate: it communicates the core return values and the default time window. It does not explain how from/to/days combine or why this tool is preferable over sibling tools, so an agent may be uncertain in edge cases.
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?
The schema already describes to, from, and days, covering 75% of parameters, and the description adds the 'full retained history' default, which complements the days parameter. Still, the site parameter is left undocumented in both schema and description, and no guidance is given on precedence when multiple time parameters are supplied.
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 identifies the resource (a site) and explicitly enumerates the headline KPIs, so an agent can understand what get_stats returns. The 'headline KPIs' wording implies an aggregate overview, which differentiates it from more specific siblings like get_timeseries or get_breakdown, though it does not explicitly name them.
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?
There is no when-to-use guidance and no mention of alternative tools. The only usage-related phrase, 'Defaults to the full retained history,' describes a parameter behavior rather than a decision rule. An agent cannot tell from this description whether to choose get_stats over get_visitors or get_bot_report.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Daily traffic series for a site (visits, visitors, pageviews, clicks, bots per day, in the site's timezone).
| Name | Required | Description | Default |
|---|---|---|---|
| to | No | ||
| days | No | ||
| from | No | ||
| site | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the behavioral burden. It discloses that results are daily series, which metrics are included, and that dates align with the site's timezone. This is meaningful behavioral context beyond the schema, though it does not address response shape, date-window defaults, or limits.
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 single compact sentence that front-loads the core purpose and packs the metrics and timezone detail into a parenthetical. Every word adds value, and there is no redundancy or fluff.
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?
The tool has four parameters, no parameter descriptions, no output schema, and no usage/alternative guidance. The description explains what data is returned but omits how to specify the requested date range and what the response looks like, so an agent cannot invoke it with full confidence.
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 description coverage is 0%, so the description must clarify parameter meaning, but it only loosely supports the 'site' parameter with 'for a site.' The date-related parameters to, days, and from are completely unexplained, leaving their formats, precedence, and interactions ambiguous.
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 identifies a daily traffic series for a site and lists the included metrics: visits, visitors, pageviews, clicks, and bots. It is set apart from siblings like get_realtime and get_breakdown by emphasizing daily granularity, though it lacks an explicit verb and does not directly name a differentiating sibling.
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?
The description implies use for daily aggregated site traffic in the site's timezone, which helps an agent distinguish it from real-time or breakdown tools. However, it provides no explicit guidance on when to choose this tool over get_stats, get_visitors, get_breakdown, or get_bot_report, and no exclusions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent individual visits: entry page, path taken, country, device, human/bot.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| site | Yes | ||
| limit | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden of behavioral disclosure. It only lists output fields and does not state whether this is a safe read-only operation, any response limits, default time windows, or pagination behavior.
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 single, front-loaded phrase with no wasted words. It immediately communicates the resource and relevant output dimensions, making it easy for an agent to parse.
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?
There is no output schema, no annotations, and only a terse description, so the agent must rely on the description for both selection and invocation. It lacks parameter semantics, sibling differentiation, and behavioral details, making it incomplete for confident tool use.
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 description coverage is 0%, yet the description does not explain the 'site', 'days', or 'limit' parameters. 'Recent' and 'individual visits' provide only weak hints about 'days' and 'limit', leaving most parameter meaning to inference.
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 identifies the resource as recent individual visits and lists the key returned fields (entry page, path, country, device, human/bot). The word 'individual' helps distinguish it from aggregate or bot-specific sibling tools, though it lacks an explicit verb like 'retrieves' or 'lists'.
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?
The phrase 'Recent individual visits' implies this tool is for detailed visitor-level data rather than aggregates, but it does not explicitly state when to prefer it over get_stats, get_realtime, or get_bot_report. No alternatives or exclusion criteria are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List the websites on this DevDome account with their verification status.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral burden. It makes the read-only listing behavior clear and discloses that verification status is included, but it does not describe the returned shape, any limitations, or whether all sites are returned. These are not severe gaps for a zero-parameter list tool, but they are unaddressed.
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?
A single, front-loaded sentence that states the action and the key output detail. There is no redundant language or schema repetition.
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?
For a no-input listing tool, the description covers what the tool does and the key returned attribute (verification status). While there is no output schema to spell out the full return structure, the description is sufficient for an agent to invoke it 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?
There are no parameters and schema coverage is complete, so the baseline is 4. The description reinforces the only meaningful scope—sites on the current DevDome account—without needing to explain any inputs.
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 names a specific action (list) and a specific resource (websites on the current DevDome account), and adds the relevant output dimension (verification status). This makes it clearly distinct from siblings like add_site, verify_site, or get_site_health.
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?
The intended use is reasonably clear: call this when you need to enumerate sites and see verification status. However, it does not explicitly state when to prefer this over sibling tools or provide exclusions, so an agent must infer the selection from the tool name and context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Verify ownership of a pending website (checks the installed snippet or DNS TXT record).
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses the verification mechanism (snippet or DNS TXT record) and the read-style nature ('checks'), which is useful. It does not address side effects, auth prerequisites, rate limits, or what the response indicates, leaving some behavioral gaps.
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?
A single sentence conveys the action, target, and mechanism with zero filler. The key scoping (pending website) is front-loaded, and the parenthetical adds explanatory detail without bloating the description.
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?
For a one-parameter tool with no output schema, the description covers the essential what, when, and how. It does not explain the return value or failure behavior, but an agent can invoke it correctly with only a domain.
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?
The only parameter, 'domain,' has no schema description (0% coverage), so the description must compensate. It implies domain is the website being verified but never mentions the parameter or its expected format (e.g., bare domain vs. protocol). It provides partial context but not full parameter semantics.
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 and resource: 'Verify ownership of a pending website.' It adds the mechanism ('checks the installed snippet or DNS TXT record'), which makes the tool's function unmistakable and separates it from the analytics and reporting siblings like get_stats and get_visitors.
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 clearly targets 'pending website,' situating the tool in the site-onboarding flow after a site has been added but not yet verified. It does not explicitly name alternatives or say when not to use it, but the context is clear enough against the sibling set.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
add_siteget_bot_reportget_breakdownget_realtimeget_site_healthget_statsget_timeseriesget_visitorslist_sitesverify_siteClaiming 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, then choose Claim with GitHub. An organization namespace such as io.github.acme/server also needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.
HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at /.well-known/glama.json on 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.
No comments yet. Be the first to start the discussion!
Add one secure layer between your agents and this server.
Each tool maps to a distinct resource or analytics view: site lifecycle (add, list, verify), aggregate stats, timeseries, top-N breakdowns, individual visitors, real-time activity, bot reports, and health. The only slight overlap is that get_stats includes bots as a KPI, but get_bot_report is clearly a dedicated classification view, so there is no real ambiguity.
All tool names follow a consistent verb_noun snake_case pattern: add_, list_, get_, verify_. The only minor variation is list_sites using a plural noun while add_site uses singular, which is a standard and predictable convention for resource collections.
Ten tools is well within the ideal range and the count matches the server's scope: site onboarding, verification, analytics reporting, and health monitoring. Each tool adds a distinct capability without redundancy or bloat.
The core workflows are covered: sites can be added, listed, and verified, with comprehensive traffic analytics including aggregates, timeseries, breakdowns, visitors, real-time activity, bot reports, and health. The main gap is the lack of site update/delete operations, but that is a minor lifecycle omission rather than a workflow-breaking issue.