canlii-mcp

Server Quality Checklist

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Latest release: v1.1.4
Disambiguation5/5
Each tool has a distinct purpose: browse_legislation lists legislation items, get_case_citator retrieves full citation relationships, get_case_citator_tease offers a quick preview, get_case_law_decisions lists decisions from a court database, get_case_metadata provides detailed case info, get_courts_and_tribunals lists available court databases, get_legislation_databases lists legislation databases, get_legislation_regulation_metadata fetches legislation details, and search performs keyword searches. No two tools overlap significantly.
Naming Consistency4/5
Most tools follow a 'get_' prefix (e.g., get_case_metadata, get_courts_and_tribunals), but 'browse_legislation' uses 'browse_' and 'search' is a bare verb. This slight inconsistency is minor and does not hinder readability.
Tool Count5/5
Nine tools is appropriate for a legal research server. Each tool covers a core function—searching, browsing cases and legislation, citators, and metadata retrieval—without being excessive or insufficient.
Completeness4/5
The surface covers essential read-only legal research operations: search, browse, citator, and metadata. Minor gaps include lack of date filters on search (mitigated by jurisdiction keywords) and no direct full-text retrieval (URLs provided instead). Overall, it's well-rounded.
Average 4/5 across 9 of 9 tools scored.
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
- Last stable release on April 9, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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?
No annotations exist, so description bears full burden. It reveals what is returned but does not disclose that it is read-only, any side effects, permissions, 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 sentences: first states purpose and content, second provides actionable instruction. No wasted words, information is front-loaded.
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 simplicity and absence of output schema, the description adequately covers the return content and user instruction. However, it could mention that the IDs come from browse results.
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?
Input schema has 100% description coverage, so the description adds minimal extra meaning beyond the schema's field descriptions. The mention of 'CanLII URL, citation, and table of contents' provides general context but not parameter details.
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 retrieves metadata for a specific statute/regulation, including URL, citation, and table of contents, distinguishing it from sibling tools like browse_legislation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (when you need metadata for a specific legislation), but does not provide explicit guidance on when to prefer this over siblings or exclude certain cases.
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, and the description does not disclose behavioral traits such as pagination, rate limits, or output size. For a listing tool, this is a significant gap.
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?
Three focused sentences: purpose, use case, and examples. No redundant information; every sentence is necessary.
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 10 parameters and no output schema, the description is adequate but lacks details on how filters interact, output format, or pagination. Suitable for a basic list tool but not fully complete.
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 coverage is 100%, but the description adds value by listing key statutes per database (e.g., 'ons: Children's Law Reform Act'), helping agents select the correct databaseId. This goes beyond the schema's pattern description.
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 lists all legislation items in a specific database and is used to find legislation IDs for metadata lookup. It distinguishes from sibling tools which focus on case law.
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 specifies using the tool to find legislation IDs, but does not explicitly state when not to use it or compare to the sibling 'search' tool. The context is clear enough for legislation-specific tasks.
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?
No annotations provided, so description carries full burden. It discloses that results are ordered by most recently added, which is key behavior. However, it does not mention any potential side effects, authorization needs, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences that front-load the main purpose and add relevant usage context. Could be slightly more structured, but overall concise.
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 12 parameters (all documented in schema) and no output schema, the description sufficiently explains the tool's purpose, ordering, and relationship to sibling tools. References get_case_metadata for full details, which helps complete the picture.
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% with clear parameter descriptions. The description adds high-level purpose but does not provide additional meaning beyond what the schema already specifies for parameters.
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?
Description clearly states the tool lists case law decisions from a specific court database, with date filtering capabilities. It explicitly distinguishes from the sibling tool get_case_metadata, which provides full details on a specific case.
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?
Provides clear context for use (browsing recent decisions from a specific court) and mentions an alternative tool (get_case_metadata) for full details. However, it does not explicitly mention when not to use this tool or other alternatives like 'search'.
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?
No annotations are provided, so the description carries the full burden. It states the tool returns database IDs and lists key databases, but it does not disclose behavioral traits such as read-only nature, rate limits, or any side effects. For a simple listing tool, this is adequate but not exhaustive.
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 plus a brief list of key databases. It is front-loaded with the purpose and provides immediate value without unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 9 optional filter parameters, but the description does not explain their purpose or how to use them effectively. There is no output schema, and the description only mentions 'returns database IDs' without specifying format or structure. This leaves some gaps, but for a simple listing tool it is minimally adequate.
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 input schema has 100% description coverage, so the baseline is 3. The description does not add meaning beyond the schema; it only mentions database IDs in the output context. The parameters are well-documented in the schema, so no further elaboration is 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's function: listing all available legislation databases in Canada. It provides specific examples of key databases and what they represent. This distinguishes it from sibling tools like browse_legislation or get_case_citator.
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 indicates the tool is for retrieving a list of databases, which is a clear use case. It does not explicitly mention when not to use it or provide alternatives, but the context is sufficient for an AI agent to understand its primary role.
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?
No annotations are provided, so the description carries the burden. It discloses the tool is a read-like retrieval (getting metadata) and includes an instruction to always provide the URL to the user. However, it does not explicitly state it is read-only or mention any permissions or side effects, which weakens transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences. The first states the purpose and output; the second gives usage guidance. Every word adds value, and the structure is front-loaded with the most critical information.
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 description lists key output fields, providing enough context for an agent to understand return structure despite no output schema. It does not explain all parameters or potential errors, but for a simple retrieval tool, it is complete enough.
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 each parameter already has a description. The tool description adds no additional meaning beyond schema, except implying that databaseId and caseId are central. This meets the baseline of 3.
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 the specific verb 'Get' and targets 'detailed metadata for a specific case'. It lists key outputs (CanLII URL, citation, etc.) and differentiates the tool from search and browsing by stating it provides complete details before citing.
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 explicitly guides the agent to use this tool 'after finding a case via search or browse to get complete details before citing it'. This provides clear context for when to invoke it, though it does not explicitly mention when not to use it or name specific alternatives.
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?
Though no annotations are provided, the description implies a read-only operation (listing databases) and explicitly states it returns database IDs. It does not contradict any annotations.
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 concise, using three sentences to convey purpose, examples, and usage guidance. Slightly verbose with examples but overall 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's simplicity and no output schema, the description covers the core purpose and return values. It does not detail the return structure but is sufficient for a listing tool.
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?
All 9 parameters are fully described in the input schema (100% coverage). The description does not add additional meaning beyond the schema, meriting a baseline score of 3.
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 lists all available court and tribunal databases in Canada and returns database IDs needed for other tools. It distinguishes itself from siblings like get_legislation_databases by specifying it provides database IDs for browse and citator tools.
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 explicitly advises using this tool to discover valid databaseId values for browse and citator tools, providing clear guidance on when to use. However, it does not mention when not to use or alternatives.
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?
No annotations are provided, so the description must disclose behavioral traits. It states 'Returns the full list of citing/cited items,' which implies a complete list without pagination. However, it does not cover potential limits, error handling, authentication needs, or response structure. For a read-only lookup tool, this is adequate but lacks depth.
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 paragraph of four sentences, front-loaded with the core purpose. Every sentence provides useful information without unnecessary words. It is highly concise and well-structured for quick comprehension.
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 12 parameters (mostly optional date filters) and no output schema, the description focuses on the essential use cases and the returned item list. It covers the critical metadataType options and the tool's importance. However, it does not mention the filtering capabilities or language parameter, which are documented in the schema but not in the description. Overall, it is sufficiently complete for an AI agent to understand the tool's core functionality.
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?
Input schema has 100% description coverage, providing clear meaning for all parameters. The description adds value by explaining the semantic intent of metadataType and the overall workflow, e.g., 'use 'citingCases' to see what later cases cite this decision.' It does not repeat parameter descriptions but enhances understanding, going beyond the baseline of 3.
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: 'Look up citation relationships for a case.' It specifies the three metadataType values and their meanings (citingCases, citedCases, citedLegislations), making the tool's function very specific and distinguishable from siblings like get_case_citator_tease, though not explicitly differentiating.
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 provides clear guidance on when to use each metadataType: 'Use 'citingCases' to see what later cases cite this decision... Use 'citedCases' to see what authorities this case relied on. Use 'citedLegislations' to see what statutes the case references.' It frames the tool as 'critical for verifying if a case is still good law,' but does not mention when not to use it or how it compares to the sibling get_case_citator_tease.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description fully compensates for missing annotations by disclosing return content (citations and titles only, not keywords/dates/URLs), search nature (keyword-based), limitations (no date filters), and recommended follow-up. No contradictions.
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?
Description is a single paragraph that covers all needed information without wasted words. Could be more structured with bullets, but each sentence adds value and it remains readable.
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 no output schema and no annotations, the description provides sufficient context: input, behavior, limitations, and workflow. It covers what the tool returns and what it does not, and directs the agent to next steps. Could mention error handling or permissions, but is complete for a search tool.
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 coverage is 100%, so baseline is 3. Description adds value by noting 'keep low for AI context efficiency' for resultCount, and explaining that query should include jurisdiction to narrow. These go beyond schema field 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?
Description clearly states the tool searches CanLII for cases, legislation, and commentary by keyword, and positions it as the primary entry point for legal research. However, it does not explicitly differentiate from sibling tools like browse_legislation or get_case_metadata, though it implies they are for follow-up after search.
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?
Provides explicit when-to-use guidance: 'primary entry point' and after search, 'call get_case_metadata on promising results'. Also explains search is keyword-based, not semantic, and advises including jurisdiction. Does not explicitly list situations where other tools are better, but the workflow is clear.
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?
Discloses the key behavioral trait of returning at most 5 results and being faster than the full citator. However, with no annotations provided, it does not cover other traits like authentication requirements or error handling, which would be valuable for a write operation but this is a read-only preview.
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?
Extremely concise with two sentences that convey purpose, limits, speed advantage, and recommended workflow. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains the tool's role and limits but does not describe the output format or behavior beyond the preview, leaving some ambiguity for an agent. However, given the simplicity of the tool and the absence of an output schema, it is minimally adequate.
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 each parameter already well-described in the schema. The description adds no further parameter-level detail beyond the tool's overall purpose, so it aligns with the baseline score.
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?
Clearly states the tool provides a quick preview of citation relationships with a maximum of 5 results, distinguishing it from the sibling 'get_case_citator' which offers the complete list.
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?
Explicitly tells when to use this tool ('quick check') and advises to use the full citator for a complete list if needed, providing clear usage context and alternatives.
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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