Matomo MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Tools have distinct purposes: generic API call, listing reports, getting metadata, processed reports, row evolution, and image graphs. However, matomo_call could be used to replicate the others, creating slight ambiguity.
Naming Consistency4/5
All tools start with 'matomo_' followed by a verb phrase. Most use 'get' for retrieval, but 'list' and 'call' deviate slightly. Pattern is clear and mostly consistent.
Tool Count5/5
6 tools is well-scoped for a Matomo analytics server. The set covers key interactions without being overwhelming, and the generic matomo_call fills any gaps.
Completeness5/5
Tools cover listing, metadata, processed data, row evolution, and graph generation. The generic matomo_call ensures any missing API method is accessible, making the surface complete.
Average 2.7/5 across 6 of 6 tools scored. Lowest: 2/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 8 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
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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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description fails to disclose any behavioral traits (e.g., destructive actions, rate limits, data scope). The description carries the full burden but adds minimal transparency beyond the basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (one sentence in Italian), but this brevity omits essential details. It is under-specified rather than concise, sacrificing usefulness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 13 parameters, no output schema, and no parameter descriptions, the description is severely incomplete. An agent cannot reliably use this tool without additional documentation.
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?
The input schema has 13 parameters with no description coverage (0%). The description does not explain any parameters, including required ones like apiModule and apiAction, leaving the agent without critical usage context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool generates a PNG image of a graph via ImageGraph.get, but it is in Italian and does not elaborate on the type of graphs or metrics. Compared to siblings like matomo_get_processed_report, the purpose is discernible but lacks clarity.
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 matomo_get_processed_report. The description does not provide any context for selecting this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden. It only states that the tool retrieves a report, but does not disclose behavioral traits such as side effects, permissions, rate limits, or constraints. Minimal transparency.
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, which is concise but lacks structure or front-loading of key information. For a tool with many parameters, it is under-specified and does not earn its length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (14 parameters, no output schema, no annotations), the description is extremely incomplete. It does not explain return values, required parameters, or how to use the tool effectively.
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%, and the description does not explain any of the 14 parameters. This fails to add meaning beyond the input schema, which itself lacks descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action (recupera = retrieves) and resource (report completo processado con dati numerici), making the purpose clear. However, it does not differentiate from sibling tools like matomo_list_report_metadata, which may also retrieve report 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 is provided on when to use this tool versus alternatives. There is no context for preferred use cases or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 burden of disclosing behavioral traits. It lacks information on side effects, authentication needs, rate limits, or any constraints. It only states what the tool does, not how it behaves.
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 very short and to the point, with no unnecessary words. It front-loads the action and result. However, it could be slightly expanded without losing conciseness to improve completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (8 parameters, no output schema, no annotations), the description is severely lacking. It does not explain how to use the parameters or what the response looks like, leaving the agent to guess or rely on external knowledge.
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?
With 0% schema description coverage, the description should explain parameters. It does not mention the key parameters apiModule and apiAction, nor does it clarify the role of date, period, or boolean options. The brief mention of 'schema, unità di misura, documenti' hints at output but not input semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves metadata for a specific report via API.getMetadata, and includes what is returned (schema, unit of measure, documents). It distinguishes from siblings like matomo_list_report_metadata by implying it targets a specific report, though it could be more explicit.
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 guidance on when to use this tool versus alternatives. No mention of prerequisites, when not to use, or how it compares to matomo_list_report_metadata or matomo_get_processed_report.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only states the basic purpose without mentioning side effects, read-only nature, authorization requirements, or limits. This is insufficient for an agent to understand the tool's behavior.
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 a single sentence that efficiently conveys the core purpose. It is front-loaded and concise, with no extraneous information.
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 has 9 parameters (4 required) and no output schema, the description is incomplete. It does not explain return values, how the evolution is presented, or any other context beyond the basic function.
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% and the description does not explain any parameters. It fails to add meaning beyond the schema structure. For a tool with 9 parameters, this omission is critical.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool analyzes temporal evolution of a single report row, using API.getRowEvolution. It specifies the verb 'Analizza' and the resource 'evoluzione temporale di una singola riga di report'. However, it does not explicitly differentiate from sibling tools like matomo_get_processed_report, which might have overlapping functionality.
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 alternatives. The description only states what it does, not the context or conditions for its use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility for behavioral disclosure. It only states that the tool executes methods, without mentioning side effects, authentication requirements, rate limits, or error behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two sentences), front-loads the purpose, and lists parameters efficiently without extraneous 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?
For a generic API caller with nested parameters and no output schema, the description is insufficient. It lacks guidance on constructing the 'params' object, error handling, and authentication context, leaving the agent underinformed.
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%, so all parameters are documented in the schema. The description merely lists parameter names without adding new semantics, meeting the baseline but adding no extra value.
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 executes any Matomo HTTP reporting API method, with specific examples (VisitsSummary.get, SitesManager.getSitesWithViewAccess). It implies a generic nature, distinguishing it from sibling tools that cover specific methods.
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 provides no guidance on when to use this tool versus sibling tools like matomo_list_report_metadata or matomo_get_processed_report. There is no mention of prerequisites, alternatives, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 of behavioral disclosure. It reveals the operation is a retrieval from an API endpoint, but does not mention side effects, required permissions, error behavior, or output structure. This is insufficient for an agent to anticipate the tool's behavior reliably.
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: two sentences that state the action and its purpose. Every word contributes meaning. No fluff or redundant information.
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?
For a tool with 6 parameters and no output schema, the description is too minimal. It does not explain what data the returned list contains, how to interpret the metadata, or how the parameters filter the results. An agent would lack context to use this tool effectively in a real scenario.
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 only 17% (idSite has a description). The tool description adds no parameter-level information beyond what is in the schema. With 6 parameters total, the agent receives no guidance on how to use date, period, language, hideMetricsDoc, or showSubtableReports, which would be essential for effective 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: 'Recupera lista completa di report compatibili da API.getReportMetadata. Utile per esplorazione.' This is a specific verb ('retrieves') and resource ('list of compatible reports') with the source API, making it easy for an agent to understand what it does and distinguish from siblings like matomo_get_metadata or matomo_get_processed_report.
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 mentions 'Utile per esplorazione' (useful for exploration), implying a general exploratory context. However, it does not explicitly state when to use this tool vs. alternatives, nor does it provide any exclusions or prerequisites. Sibling tools are listed but not compared.
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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