mcp-server-corpayone

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.0.1
Disambiguation5/5
Each tool has a distinct purpose: connection check, generic endpoint call, committing prepared writes, listing expenses/webhooks, preparing expense coding or webhook changes, and searching capabilities. Descriptions clearly differentiate them, with no overlapping functionality that would cause confusion.
Naming Consistency5/5
All tools follow a consistent 'corpay_verb_noun' pattern using snake_case, such as 'corpay_list_expenses' and 'corpay_prepare_webhook_change'. Verbs are descriptive and uniform, making the tool set predictable and easy to navigate.
Tool Count5/5
With 8 tools, the server is well-scoped for its purpose of interacting with the Corpay One API. Each tool covers a necessary function (authentication, listing, preparing, committing, searching) without unnecessary bloat or gaps.
Completeness4/5
The tool set covers core workflows including listing, preparing, and committing operations. However, direct 'get' operations for individual expenses or webhook subscriptions are missing, requiring use of the generic endpoint call tool. This minor gap prevents full CRUD coverage.
Average 3.7/5 across 8 of 8 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 19 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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=false and openWorldHint=true. The description adds that the endpoint is validated and allowlisted, and clarifies the read-only behavior is conditional on write policy. However, it does not describe response format, error handling, or cancellation 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 extremely concise with two sentences, covering purpose and a usage condition. However, it sacrifices necessary detail about parameters.
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 no output schema and 0% parameter coverage, the description fails to provide essential context for a 6-parameter tool. The agent lacks guidance on how to construct requests, making the tool difficult to invoke correctly.
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%. The description provides no explanation of the six parameters (body, query, method, pathParams, pathTemplate, idempotencyKey). An agent cannot infer their meaning or usage from the description alone.
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 that the tool calls a validated, allowlisted endpoint. The verb 'call' and resource 'endpoint' are precise, and the tool's generic nature distinguishes it from sibling tools like corpay_list_expenses or corpay_check_connection.
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 offers limited guidance on when to use this tool versus siblings. It mentions read-only unless write policy permits, which hints at safe usage, but lacks explicit when-to-use or when-not-to-use instructions.
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 indicate readOnlyHint=true and openWorldHint=true, so the description's 'List expenses' adds no further behavioral context. It does not disclose pagination, latency, or result limits. With annotations covering the core behavioral traits, the description adds minimal extra 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?
Two sentences, front-loaded with the verb and resource, followed by the filtering usage. No extraneous words; every sentence earns its place.
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 a simple list tool with one optional parameter and no output schema, the description is adequate but incomplete. It does not address pagination, result format, or handling of complex nested query objects. For a tool with nested object parameters, more detail would be beneficial.
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 0%, so the description must compensate. It provides a concrete example of how to use the query parameter ('status=pending_approval'), which adds meaning beyond the abstract schema definition. However, it does not explain all possible filter keys or the structure of nested objects.
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?
Title and description clearly state the verb 'list' and resource 'expenses', with parenthetical clarification 'bills/documents'. While not explicitly differentiating from sibling tools, none are similarly named, so the purpose is clear.
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?
Provides an example of filtering usage ('status=pending_approval') but lacks when-not-to-use guidance or comparison with sibling tools like corpay_prepare_expense_coding. The use case is implied but not fully explicit.
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 context beyond the readOnlyHint annotation by specifying the dry-run nature (no actual changes) and that the output is a hash for commitment. It does not detail error behavior or idempotency, but the annotation already covers read-only safety.
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 two-sentence description is concise but omits vital parameter semantics, making it too brief for a tool with four parameters and no output schema. The structure front-loads the key 'Dry-run' concept, but the lack of parameter info undermines conciseness.
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?
The description is incomplete for the tool's complexity: 0% schema coverage, no output schema, and no mention of error cases or parameter details. It only partially covers the return value (operationHash) and omits essential usage context.
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?
With 0% schema coverage and no parameter descriptions in the description, the agent receives no guidance on the meaning or format of body, method, reason, or webhookId. This is a critical gap given the tool has four 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?
The description clearly states the tool performs a dry-run of create, update, or delete operations on webhook subscriptions, and that it returns an operationHash for later commitment. This distinguishes it from sibling tools like corpay_list_webhooks and corpay_commit_prepared_operation.
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 term 'Dry-run' explicitly signals a preview mode before committing changes, which guides the agent to use this tool for testing rather than direct modification. The mention of 'operationHash to commit' implies a follow-up step, though it does not name the sibling commit tool explicitly.
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 declare readOnlyHint=true and openWorldHint=false. The description adds the specific search context but no additional behavioral details like pagination, rate limits, or what happens with an empty query.
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?
Single sentence with no redundant text. Could be slightly improved by briefly mentioning the query parameter's role, but overall efficient.
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?
Adequate for a simple search tool with no output schema. Lacks details on input behavior (e.g., case sensitivity, partial matching) but covers the basic purpose.
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 0%. The description does not explain the 'query' parameter's meaning or behavior (e.g., what empty query returns, how to format). Relies entirely on the parameter name.
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 'Find supported tools and allowlisted endpoint operations' clearly states the tool's purpose with a specific verb ('find') and resource ('tools' and 'endpoint operations'). It distinguishes from sibling tools like corpay_call_endpoint which executes calls.
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. The purpose implies it's for discovery, but no 'when not to use' or references to siblings 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 state readOnlyHint=true and openWorldHint=true, so the safety and variability are covered. The description adds that only 'active' subscriptions are listed, but does not mention pagination, limits, or response format.
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 that efficiently communicates the tool's purpose without unnecessary 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?
For a simple read-only list tool with no input parameters, the description adequately states what it returns and the scope. However, it lacks details on response structure or any constraints, though no output schema exists to compensate.
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 baseline 4 applies. The description does not need to add parameter info.
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 lists active webhook subscriptions for the configured team, using a specific verb and resource. It distinguishes itself from the sibling tool 'corpay_prepare_webhook_change' which modifies webhooks.
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 alternatives like 'corpay_prepare_webhook_change' or when to list webhooks. No context about prerequisites or conditions is given.
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 indicate readOnlyHint=false, destructiveHint=true, openWorldHint=true. The description adds that the write is 'policy-checked' and requires idempotencyKey, which provides some additional context but does not elaborate on what gets destroyed or side effects. No contradiction 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 a single sentence that is front-loaded with the core purpose ('Execute a prepared, policy-checked write') followed by required inputs. Every word contributes value with 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?
Given the tool's complexity (3 required params, no output schema, destructive nature), the description covers the main action and inputs but does not specify return values, success indicators, or sync/async behavior. It's mostly complete but could add a note on what to expect after execution.
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% schema coverage, the description compensates by explaining the purpose of each parameter: operation is the 'full prepared operation', confirmOperationHash must match, and idempotencyKey ensures idempotency. This adds meaning beyond the bare schema, though type details are lacking.
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 a prepared, policy-checked write. It specifies the required inputs (operation, confirmOperationHash, idempotencyKey). The verb 'execute' and resource 'prepared operation' are precise, and the name itself distinguishes it from sibling prepare tools.
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 use after a preparation step but does not explicitly state when to use this tool versus its siblings (e.g., corpay_prepare_expense_coding). It lacks exclusions or alternative guidance, relying on the implied context from the tool name.
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 key behavior: dry-run, no call to Corpay One until committed, returns operationHash. Annotations indicate readOnlyHint=true, which aligns with no side-effects until commit. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two effective sentences front-loading purpose and behavior. No fluff; every word adds value.
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?
Adequate for a simple tool with no output schema, but parameter explanations are missing. Workflow is clear, but parameter semantics are incomplete.
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 coverage is 0%. Description mentions categories and labels, suggesting body content, but does not explain expenseId or reason. Lacks explicit mapping to 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?
Clearly states the tool is a dry-run update for expense coding (GL account and labels), returns an operationHash, and does not commit until later. Differentiates from sibling corpay_commit_prepared_operation.
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?
Implies usage: prepare then commit. Lacks explicit when-not-to-use or alternatives, but the dry-run nature and hash return clearly guide the workflow.
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 and openWorldHint are true. The description adds that the tool acquires an access token and that no teamId is needed, providing context beyond the 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 sentence that is clear and concise, with no unnecessary 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?
Given the tool has no parameters and no output schema, the description adequately explains its function. However, it could mention what the tool returns (e.g., success/failure) for full completeness.
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 schema coverage is 100%. The description adds value by clarifying that no teamId is required, which is useful for agent understanding.
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 OAuth credentials by acquiring an access token, which distinguishes it from sibling tools that perform other actions like calling endpoints or listing expenses.
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 it does not require a teamId but does not explicitly state when to use this tool versus alternatives, such as before making other API calls or for troubleshooting.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![mcp-server-corpayone MCP server](https://glama.ai/mcp/servers/borgels/mcp-server-corpayone/badges/card.svg)](https://glama.ai/mcp/servers/borgels/mcp-server-corpayone)

Score Badge

Copy to your README.md:

[![mcp-server-corpayone MCP server](https://glama.ai/mcp/servers/borgels/mcp-server-corpayone/badges/score.svg)](https://glama.ai/mcp/servers/borgels/mcp-server-corpayone)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/borgels/mcp-server-corpayone'

If you have feedback or need assistance with the MCP directory API, please join our Discord server