Umami MCP Server

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool serves a distinct purpose: searching, listing, validating, and retrieving various analytics metrics (active visitors, breakdown, events, pageviews, stats). No overlap or ambiguity.
Naming Consistency5/5
All tool names follow a consistent 'umami_verb_noun' pattern (e.g., umami_find_website, umami_get_active). The pattern is uniform and predictable.
Tool Count5/5
With 8 tools, the set is well-scoped for an analytics API. It covers essential query operations without being bloated or sparse.
Completeness5/5
The tool set provides comprehensive read-only access to Umami analytics: website listing/search, active visitors, pageviews, events, breakdowns, stats, and authentication validation. No obvious gaps for querying use cases.
Average 4/5 across 8 of 8 tools scored. Lowest: 3.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, so the safety profile is clear. The description adds that it returns rows with event name, timestamp, and count, but does not disclose any additional behavioral traits beyond what annotations provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences with no wasted words. It is efficiently structured, though it could benefit from slightly more detail on output structure.
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?
Given the absence of an output schema, the description partially explains the return values (event name, timestamp, count rows) but lacks detail on the exact data structure (e.g., whether it's an array, how fields are named). For a tool with moderate complexity, this is somewhat incomplete.
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 description coverage is 100% with detailed parameter descriptions (e.g., websiteId referencing other tools, startAt/endAt examples, unit enum). The description adds minimal extra semantic information, so it is adequate but not exceptional.
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 gets custom event counts over time for a website, with a specific resource (custom events) that distinguishes it from sibling tools like umami_get_pageviews (pageviews) and umami_get_breakdown (breakdown data).
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 on when to use this tool versus alternatives like umami_get_pageviews or umami_get_stats. The description only explains what it does without contextualizing when it is the best choice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description carries less burden. It adds the specific time window ('last 5 minutes'), which is a useful behavioral detail beyond the annotation.
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?
A single, concise sentence that contains no filler or redundant information. Every word adds value.
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?
For a simple read-only tool with one parameter and no output schema, the description is fairly complete. It specifies the metric and time window, and the parameter description provides guidance on how to find the websiteId. However, it does not explicitly state the return type (e.g., integer).
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?
The schema has 100% description coverage, so the baseline is 3. The tool description adds no additional meaning about the parameter; the parameter's own description already explains how to obtain the websiteId.
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 specific verb (Get), resource (active visitors), and scope (last 5 minutes), distinguishing it from siblings like umami_get_pageviews or umami_get_stats.
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?
The description does not provide any guidance on when to use this tool versus alternatives, nor does it mention when not to use it. The parameter description hints at prerequisites but the main description lacks usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already indicates the tool is read-only. The description adds no additional behavioral context (e.g., authentication, rate limits, error handling) beyond stating the action, which is consistent with the annotation.
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 consists of two short sentences that front-load the main purpose and list return values. Every word is necessary and informative, with no redundancy or extraneous details.
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?
The tool has no output schema, so the description's list of return metrics provides essential context. Combined with the rich input schema descriptions and readOnlyHint, it is largely complete. Minor gap: no indication of the response structure or aggregation details, but it suffices for agent invocation.
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 description coverage is 100% with detailed parameter descriptions (e.g., examples for dates, explanations for websiteId). The tool description adds no extra parameter semantics; its mention of returned metrics pertains to output, not input parameters. Baseline 3 applies per guidelines.
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 'Get summarized Umami stats' and specifies the resource 'a website and time range', along with listing the returned metrics (pageviews, visitors, visits, bounces, totaltime, comparison data). This effectively distinguishes it from sibling tools like umami_get_pageviews or umami_get_breakdown.
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 the tool is for obtaining aggregate stats over a period, but it does not explicitly state when to prefer this tool over alternatives, nor does it mention when not to use it. No comparison 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true; the description adds value by specifying return fields (id, name, domain, createdAt) but does not disclose additional behaviors like pagination or rate limits.
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 concise sentences front-loaded with the action and result, no wasted words.
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?
Complete for a simple list operation given no parameters, readOnlyHint annotation, and no output schema; could mention if the list includes all websites or is paginated.
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?
With 0 parameters, baseline is 4. The description adds meaning by detailing the returned fields, surpassing the schema's minimal coverage.
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 uses a specific verb 'List' and clearly identifies the resource 'Umami websites', distinguishing it from sibling tools like 'umami_find_website' which implies searching.
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 on when to use this tool versus alternatives such as 'umami_find_website' for searching specific websites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare 'readOnlyHint: true', so the description does not need to restate that. The description adds some behavioral context about the two modes (detailed vs x/y breakdown rows), but it does not disclose other behavioral traits like rate limits, data freshness, or pagination behavior that might be relevant. No contradictions 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at two sentences, with the purpose front-loaded. Every sentence adds value: the first states the core functionality, and the second provides key usage guidance on the 'expanded' parameter. No unnecessary words or repetition.
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?
Given the tool's complexity (8 parameters, nested filters, enum for 'type') and the absence of an output schema, the description is fairly complete. It covers the main purpose and the critical 'expanded' parameter. However, it could be more complete by briefly noting that other parameters (like 'type' and 'filters') are documented in the schema, but the description relies on the schema for those details, which is acceptable.
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 description coverage is 100%, so the baseline is 3. The description adds value beyond the schema by explaining the distinction between 'expanded=true' and 'expanded=false' (detailed metrics vs x/y breakdown rows). This clarifies the parameter's effect on the output format, which is not fully covered in 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 tool's purpose: 'Get a metric breakdown for a website and time range.' It specifies the resource (metric breakdown), action (get), and scope (website and time range). It also distinguishes between two modes ('expanded=true' vs 'expanded=false'), which differentiates it from siblings.
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 provides guidance on when to use the 'expanded' parameter, but it does not explicitly state when to use this tool versus alternative tools like 'umami_get_stats' or 'umami_get_pageviews'. It lacks exclusions or alternative recommendations, making the usage context clear but incomplete.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, and the description aligns with a read operation. It adds useful context about the type of data returned (time series) and supported features. No behavioral traits are contradicted, and the description provides additional value beyond annotations.
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 main purpose. Every sentence adds value without redundancy. Highly efficient.
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?
Given the tool has 7 parameters (4 required) and no output schema, the description covers the main features. However, it does not mention the output format, which would be helpful since no output schema is provided. Still, it is mostly complete.
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 description coverage is 100%, so baseline is 3. The description mentions time bucketing, timezone, comparison, and filters, which corresponds to parameters, but does not add new meaning beyond what the schema already provides.
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 retrieves 'pageview and session time series', using a specific verb and resource. It lists supported features (time bucketing, timezone, etc.), distinguishing it from sibling tools like umami_get_stats (aggregates) or umami_get_breakdown (dimension breakdown).
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 does not explicitly state when to use this tool versus alternatives. While it lists features, it lacks guidance on when not to use it or which sibling to choose instead, leaving the agent to infer from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds fuzzy matching behavior beyond the readOnlyHint annotation. However, it does not mention the return format or if there are limits, but for a simple search it is sufficient.
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 concise sentence with a clear usage hint, no wasted 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?
Given the simple tool with one parameter, readOnly annotation, and no output schema, the description provides all essential information: purpose, usage context, and parameter meaning.
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% and the query parameter is already well described in the schema. The description adds minimal extra meaning beyond 'search by name or domain'.
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 searches for Umami websites by name or domain using fuzzy matching, and the title confirms 'Find Umami Website'. It is distinct from siblings which are get/list operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Useful before calling other analytics tools,' providing clear context for when to use this tool versus the other tools available.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, and the description confirms it is a read operation by specifying what it returns. It adds operational context about the return values beyond annotations.
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, focused sentence that efficiently conveys the tool's purpose and return values with no wasted 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?
Given no parameters, no output schema, and the simple nature of the tool (validation), the description fully covers what an agent needs to know: what it does and what it returns.
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 no parameters, so the baseline is 4. The description correctly provides no parameter information as none are needed.
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 validates Umami configuration and authentication, listing specific return fields (auth mode, API base URL, instance URL, default timezone, current user info). This distinguishes it from sibling tools that retrieve analytics data.
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 after configuration to check connectivity, but does not explicitly state when not to use it or suggest alternatives. It is clear enough for basic guidance.
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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