BharatPay MCP

by angelina10504

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Latest release: v0.1.0
Disambiguation5/5
Each tool addresses a unique Indian financial or address validation task, with no overlap. IFSC, PAN, GSTIN, pincode, mutual fund NAV, UPI VPA, and INR formatting are all distinct and clearly separated.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern (e.g., lookup_ifsc, validate_gstin, format_inr). Verbs like 'lookup', 'validate', 'get', and 'format' are used appropriately, with no mixing of conventions.
Tool Count5/5
Seven tools is an appropriate number for a focused domain of Indian financial utilities. Each tool covers a key operation, and the count is neither too sparse nor excessive.
Completeness5/5
The tool set covers common Indian financial identifiers (IFSC, PAN, GSTIN, UPI), address lookup (pincode), mutual fund data, and currency formatting. This appears comprehensive for the intended use case, with no obvious missing operations.
Average 4.1/5 across 7 of 7 tools scored. Lowest: 3.5/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit 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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully convey behavior. It mentions 'free India Post API' hinting at external dependency and potential unreliability, but it does not disclose failure modes, rate limits, or idempotency.
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 sentence with no wasted words, effectively communicating the tool's purpose.
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 an output schema (not shown) and describes returned data. However, it lacks guidance on error handling, invalid inputs, or network issues, which for a simple tool is adequate but not fully comprehensive.
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 parameter description in the schema is clear. The tool description adds no additional meaning beyond the schema's own 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 verb 'look up', the resource 'state, district, and post offices', and specifies the API source. It is distinct from sibling tools that handle bank branches or validation.
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?
Usage is implied by the tool's specific domain (Indian PIN codes), but the description does not explicitly state when to use it versus alternatives, nor does it mention when not to use it.
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 fully disclose behavior. It mentions validation and entity identification but omits what happens on invalid input (e.g., error, null), auth requirements, or side effects. For a tool with no annotations, this is insufficient.
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?
One sentence, front-loaded, no extraneous words. Efficiently conveys core purpose.
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?
Has output schema but description does not elaborate on return values. Missing behavioral details like error handling. Adequate for a simple tool but could be more 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% with a clear example. The description adds general purpose but no additional parameter-specific detail. Baseline 3 for high 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 clearly states the tool validates Indian PAN format and identifies entity type from the 4th character. It is specific and distinct from sibling tools which handle IFSC, GSTIN, etc.
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?
No explicit guidance on when to use this tool vs alternatives. However, sibling tools are for different entities (IFSC, GSTIN, pincode), so usage is implied. Lacks when-to-use or when-not-to-use statements.
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 discloses that the tool performs a read-only lookup via Razorpay's public API, but omits details like rate limits, authentication, error handling, or data freshness. This is adequate for a simple lookup 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 two concise sentences, front-loaded with the primary action and key data returned. Every word serves a purpose, with no redundancy or fluff.
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 that an output schema exists, the description does not need to detail return values. It sufficiently covers the tool's purpose, data fields, and data source. For a straightforward lookup tool with one parameter, this is 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?
The input schema has 100% coverage with a description for the sole parameter. The tool description adds value by providing context (Indian IFSC, example format 'KKBK0000261') and mentioning the API source, going beyond what the schema alone offers.
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: looking up bank, branch, address, and payment rails for an Indian IFSC code. It explicitly differentiates from siblings (PAN, GSTIN, pincode, etc.) by specifying its unique resource.
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 for querying IFSC codes but does not explicitly state when to use vs. alternatives, nor does it mention exclusions or prerequisites. Siblings are distinct enough that no conflict arises, but some guidance would improve clarity.
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?
With no annotations, the description transparently details the tool's operations: validation of format and checksum, extraction of state and PAN, and return of state name. It does not cover error handling or rate limits, but the core behavior is well-described.
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 with two sentences, front-loading the purpose and key details. Every sentence adds value without redundancy.
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 single parameter, presence of an output schema, and clear description of validation logic, the description is nearly complete. It could briefly mention what happens on invalid input, but overall it is adequate.
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%, and the description adds meaning by specifying the parameter is a 15-character GSTIN with an example '29AABCT1332L1ZS', clarifying the format beyond the schema's 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 it validates Indian GSTIN, including format and checksum, and extracts state and PAN. It distinguishes itself from sibling tools like validate_pan by focusing on GSTIN.
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 provide explicit guidance on when to use this tool versus alternatives, such as validate_pan or lookup_pincode. The context of sibling tools suggests distinct purposes, but the description lacks proactive usage advice.
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 discloses the core behavior: format validation and PSP/bank identification via suffix mapping. With no annotations, it provides good transparency, though it omits details on error handling or limitations (e.g., doesn't check VPA existence).
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?
Single sentence, no wasted words, front-loaded with action (validate) and result (identify). Example is concise and illustrative.
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?
For a simple tool with one parameter and an output schema, the description fully covers what the tool does. It explains format and mapping, which is sufficient given output schema exists.
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 explaining the expected format ('username@psp') and providing an example that maps suffix to PSP and bank. This enriches parameter understanding beyond the bare 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 validates UPI VPA format and identifies PSP and bank from handle suffix, with an explicit example. This distinguishes it from sibling tools that handle other identifiers (IFSC, PAN, GSTIN, etc.).
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?
Usage is implied (when you have a UPI VPA), but no explicit guidance on when not to use it or alternatives. Sibling tools are different, but no comparative instructions.
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?
No annotations are provided, so the description carries the responsibility. It discloses the formatting behavior (lakh/crore grouping, word form) and the paise toggle. It could be more explicit about the exact return format (e.g., string structure), but overall it gives good insight.
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 efficient sentences: first sentence states the main purpose and formatting style, second explains the optional parameter. No redundancy.
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 formatting tool with an output schema, the description covers the essential behavior. It could elaborate on the exact output structure (e.g., returns both formatted number and word form?), but the provided details are sufficient for use.
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%, and the description adds context for 'paise' by explaining the Razorpay API convention (1 INR = 100 paise). The 'amount' parameter description is minimal but schema covers it.
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 formats an INR amount using Indian numbering conventions (lakh/crore grouping) and returns word form. It is distinct from sibling tools which are lookups/validations.
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 explains when to use the tool (formatting INR amounts) and explains the 'paise' parameter for Razorpay API style. However, it does not provide explicit when-not-to-use or alternatives, but the sibling tools are unrelated.
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 data source (AMFI India's public daily file) and that it returns the latest daily NAV. No annotations exist, so description carries the burden—it is sufficient for a simple lookup tool, though could mention caching 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, no wasted words. Immediately states purpose, then input options, then data source. Front-loaded with key info.
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?
Output schema exists, so return values are covered. Description explains input types and data source. Could mention that NAV is typically from the previous day, but overall adequate for the tool's simplicity.
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 covers 100% with parameter description. Description adds value by specifying 'digits only' for code and 'fuzzy search' for name fragment, which is not in schema. Baseline 3, plus 1 for extra context.
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 it gets the latest daily NAV for an Indian mutual fund scheme, with specific verb and resource. Sibling tools are distinct financial info tools (IFSC, PAN, etc.), so no ambiguity.
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?
Describes two valid input types (AMFI code or name fragment). Though it doesn't explicitly state when not to use, the sibling tools are in different domains, making usage context clear without additional 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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