mkopo-mcp
Server Quality Checklist
Latest release: v0.1.3
- Disambiguation4/5
Tools are mostly distinct: alternative_credit_score and mpesa_creditworthiness both use M-PESA data but one yields a score and the other analyzes patterns; credit_report_summary overlaps slightly but is a different product. Overall, an agent can differentiate them with clear descriptions.
Naming Consistency5/5All tool names follow a consistent snake_case pattern using descriptive noun phrases (e.g., loan_eligibility, credit_report_summary). No mixing of conventions or verb styles.
Tool Count5/55 tools is an ideal scope for a credit assessment server, covering score estimation, improvement tips, report summary, eligibility check, and transaction pattern analysis without unnecessary bulk.
Completeness5/5For a demo product, the tool set covers the full lifecycle of credit assessment: analysis, scoring, reporting, eligibility, and improvement. There are no obvious gaps for the stated purpose.
Average 3.9/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 36 commits in the last 12 weeks
- Last stable release on
- 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.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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?
Annotations already declare readOnlyHint=true, and the description adds no additional behavioral details such as data sensitivity, rate limits, or side effects. The term 'Generate' implies a read-only operation, but the description fails to disclose any traits beyond what is already captured in annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences plus a parallel reference. The 'DEMO educational content' note adds a minor distraction but does not significantly harm conciseness. Nearly every sentence serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the full schema coverage, output schema existence, and clear purpose, the description is nearly complete. It could mention output format briefly, but the output schema already covers that. The context is adequate for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already defines all four parameters with descriptions. The tool description adds no extra meaning or nuance to the parameters, resulting in baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Generate actionable credit improvement tips personalised to the user's situation', specifying a distinct verb and resource. It is easily distinguished from siblings like 'credit_report_summary' (summary) and 'loan_eligibility' (eligibility), which address different needs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The Western parallel to Credit Karma provides a useful analogy for when to use the tool. However, it lacks explicit guidance on when not to use it or how it compares to alternatives, missing the high bar of explicit exclusions and 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?
Annotations indicate readOnlyHint=true, and the description adds critical behavioral context: 'DEMO — not actual loan offers.' This discloses the tool's non-production nature, which is valuable 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, zero waste. First sentence states core function, second provides context and demo caveat. Efficiently structured for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present and annotations covering safety, the description is adequate for a demo tool. It could elaborate on the format of the estimate, but completeness is sufficient given the demo nature.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all 4 parameters. The description does not add further detail beyond what the schema provides, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it estimates loan eligibility for Kenya lenders, with a Western parallel and a demo notice. It distinguishes from sibling tools focused on credit scores and tips, but could be more specific about the nature of eligibility estimation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for estimating loan eligibility, but does not explicitly state when to use versus alternatives like alternative_credit_score or mpesa_creditworthiness. The Western parallel provides context but no exclusion guidance.
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 mark readOnlyHint=true. The description adds that it's a DEMO, which clarifies the fake nature. No contradictions; the description complements annotations by stating it's not a real product.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences front-load the purpose and caveat. No redundant information; every part earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the demo nature and presence of output schema, the description sufficiently covers the tool's purpose and caveat. It explains what the tool does, its analogy, and its non-production status.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all 6 parameters. The description adds no additional parameter meaning beyond what the schema provides, so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates a structured credit report summary, compares it to Experian/Equifax, and notes it's a demo. It distinguishes from siblings like alternative_credit_score (score only) and loan_eligibility (eligibility check).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus siblings. The description does not indicate when a full summary is preferred over alternative scores or tips. The DEMO note implies it's for testing but not for production use cases.
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. The description adds context: it requires simplified inputs (no raw data), is a demo, and needs customer consent, which goes 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences that efficiently convey purpose, input constraints, western parallels, and usage caveat. No unnecessary words, but the parallels provide marginal value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 required params, output schema exists, and annotations provide readOnlyHint, the description adequately covers purpose, input nature, demo status, and consent requirement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 only mentions 'simplified transaction summary inputs' without adding details beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it analyses M-PESA transaction patterns to assess creditworthiness, with a specific verb and resource. It distinguishes from sibling tools like alternative_credit_score by focusing on M-PESA-specific data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for M-PESA transaction analysis and mentions Western parallels, but it lacks explicit when-not or alternatives to sibling tools.
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 provide readOnlyHint=true. The description adds context: inputs are self-reported, it's not a real product, and mentions the real implementation would require licensed APIs. This goes 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a few sentences, front-loaded with purpose. It is clear and without waste, though could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, the description does not need to explain return values. It adequately covers the demo nature, input self-reporting, and data source considerations, making it complete for the context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with all parameters documented. The description does not add extra parameter details beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool estimates an alternative credit score from M-PESA behavioural signals, provides a Western parallel (FICO/Nova Credit), and distinguishes it as a demo. This is a specific verb+resource with useful context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when needing an alternative credit score for M-PESA users, and explicitly notes it's a demo. It does not directly state when not to use or mention alternatives, but the clarity of purpose effectively guides usage.
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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