Skip to main content
Glama
kevi-ai

AI Bounty Board MCP Server

by kevi-ai

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clear, distinct role: listing, retrieving details, viewing stats, claiming, and submitting work. No overlap in purpose.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (list_bounties, get_bounty, get_stats, claim_bounty, submit_work).

    Tool Count5/5

    Five tools is well within the ideal 3-15 range and appropriate for a focused bounty board workflow.

    Completeness4/5

    The core workflow of viewing, claiming, and submitting bounties is covered. A minor gap is no way to list one's own claims or submissions, but this is not critical.

  • 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
    • 0 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available
  • 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.

    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

  • Behavior2/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations provided, the description carries the full burden of disclosing behavioral traits. It states the action 'claim' but does not mention that this is a write/mutation operation, any on-chain implications, reversibility, or what happens after claiming. The only added context is the requirement for a wallet address, which is minimal.

    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 sentences, front-loaded with the core purpose, and contains no fluff. Every word contributes to the meaning.

    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 the tool's low complexity and full schema coverage, the description is minimally adequate. However, with no annotations or output schema, it does not explain the result of claiming, side effects, or how it fits into the overall workflow with sibling tools. This leaves some gaps.

    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 described adequately. The description adds no additional meaning beyond what the schema already provides; it simply restates that an ID and wallet are needed. 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 clearly states the action: 'Claim a bounty to work on it.' The verb 'claim' is specific and distinguishes it from siblings like list_bounties, get_bounty, and submit_work. It also identifies the resource (a bounty).

    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 the tool is used when you want to work on a specific bounty, and that you need the bounty ID and wallet address. However, it does not explicitly say when to use it versus alternatives, nor does it mention prerequisites like first looking up the bounty via get_bounty.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations provided, the description carries the full burden. It mentions required inputs but does not disclose whether submission is final, if it can be updated, whether prior claiming is required, or any side effects. For a submission/mutation tool, this is a significant transparency 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?

    The description is a single sentence that front-loads the purpose and key requirements. Every word adds value with no redundancy or fluff.

    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 covers the core action and required parameters, but without annotations or an output schema, it omits important context like prerequisites (e.g., must have claimed the bounty) and post-submission behavior. It is minimally viable but leaves gaps for an agent.

    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 clear description. The description adds only a minor hint that proof URL is 'usually GitHub', but otherwise restates what the schema already provides. Baseline 3 is appropriate.

    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 'Submit completed work for a bounty' with a specific verb and resource. It distinguishes itself from sibling tools like claim_bounty by focusing on the submission step rather than claiming.

    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 gives clear context about when to use (after completing work) and mentions the need for proof URL and description. However, it doesn't explicitly state when not to use or provide alternative tools, so it stops short of full explicit guidance.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are provided, so the description carries the full burden. It only states 'Get detailed information', which is the purpose rather than behavioral disclosures such as whether auth is required, error handling for invalid IDs, or the exact response structure. This is minimal transparency.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single, front-loaded sentence with no redundant phrasing. Every word contributes to clarity, making it appropriately 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?

    For a simple get-by-ID tool with one parameter and no output schema, the description sufficiently conveys the core functionality and expected input. It doesn't enumerate what 'detailed information' includes, but this is a minor gap given the simplicity of the operation and clear sibling differentiation.

    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%: the 'id' parameter is documented with type and example. The description mentions 'by its ID' but adds no new semantic meaning beyond the schema, so it remains at the baseline for high schema 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?

    Description uses a specific verb 'Get' and resource 'bounty' with a clear qualifier 'by its ID', distinguishing it from siblings like list_bounties. It clearly states the action and scope.

    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 phrase 'specific bounty by its ID' clearly implies this should be used when you have a bounty ID and need details, in contrast to list_bounties. However, it doesn't explicitly name alternatives or provide exclusion criteria, so it stops short of a 5.

    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 mentions filtering behavior but does not explicitly disclose that it is read-only, the return format, or potential limitations (e.g., pagination). The 'List' verb implies non-mutation, but richer context would be needed for a higher score.

    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 primary purpose, and every word adds value. No fluff or 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 list tool with two optional parameters and no output schema, the description adequately covers purpose and filters. It could mention what is returned (e.g., a list of bounty objects), but given low complexity, it is sufficiently 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 coverage is 100% (both parameters have descriptions and enums), so baseline is 3. The description mentions the same status and tag filters but adds no extra meaning beyond the 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 a specific verb ('List') and resource ('bounties from the AI Bounty Board'), and it distinguishes from siblings like get_bounty by indicating it lists all bounties rather than retrieving a single one.

    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?

    It is clear that this tool is for listing bounties with optional filters, and the context of sibling tools (get_bounty for single records) implies when to use it. However, it does not explicitly exclude alternatives or state 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.

  • 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 of behavioral disclosure. It does specify the returned fields, which is useful, but it does not explicitly state that the operation is read-only or mention any access requirements, rate limits, or potential side effects. For a simple read tool, this is adequate but not fully transparent.

    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 front-loads the primary purpose ('Get platform statistics') and then lists key data fields. Every word adds value, and there is no redundant information.

    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 zero-parameter tool with no output schema, the description fully covers the return values and overall purpose. It specifies exactly what statistics are included, making it complete for an AI agent to decide when and how to invoke it.

    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 tool has zero parameters, so the baseline score is 4. The description correctly omits parameter details, as there is nothing to explain.

    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 platform statistics and enumerates specific data points (total bounties, open count, completed count, total rewards). This distinguishes it from sibling tools like list_bounties or get_bounty, which focus on individual bounties rather than aggregate metrics.

    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 implies usage when aggregate platform metrics are needed, but it does not explicitly contrast with sibling tools or state when not to use it. The context is clear, but it lacks explicit exclusions or alternative mentions.

    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

bounty-mcp-server MCP server

Copy to your README.md:

Score Badge

bounty-mcp-server MCP server

Copy to your README.md:

Latest Blog Posts

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/kevi-ai/bounty-mcp-server'

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