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OjasKord

Tender MCP

by OjasKord
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JavaScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.3.4

  • Disambiguation5/5

    The two tools have clearly distinct purposes: search_tenders finds active tenders and provides an initial verdict, while get_tender_intelligence provides deeper competitive context on a specific tender. Their descriptions and usage guidance make disambiguation straightforward.

    Naming Consistency5/5

    Both tool names follow a consistent verb_noun pattern with underscores (search_tenders, get_tender_intelligence), using clear verbs and nouns that reflect their functionality.

    Tool Count4/5

    With only 2 tools, the server is minimal but focused on core procurement discovery tasks. While slightly below the typical 3-15 range, the narrow scope justifies the small count.

    Completeness3/5

    The server covers search and intelligence gathering, which are critical early steps, but lacks tools for acting on tenders (e.g., bidding, tracking). This leaves the workflow incomplete for end-to-end procurement support.

  • Average 4.6/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 45 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 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

  • Behavior4/5

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

    No annotations are provided, so the description carries full burden. It fully explains the two modes (AWARD_HISTORY and DAILY_DIGEST) and contextualizes their purpose. It also warns about the irreversibility of mispriced bids. However, it does not mention any rate limits, authentication requirements, or data freshness guarantees, which could be important for an agent.

    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 well-structured with a clear lead sentence, followed by usage context, mode explanations, and a strong warning. It uses bullet points for the two modes, making it scannable. While it could be slightly more concise, every sentence contributes value, and it 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.

    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 (not shown but mentioned), the description does not need to explain return values. It effectively covers all aspects: purpose, usage context, mode details, required parameters, and consequences. For a complex tool with two distinct modes, it provides complete context for an agent to make informed decisions.

    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 the baseline is 3. The description adds significant meaning beyond the schema by explaining the purpose of each mode and the consequences of not using award history. It provides context that helps the agent choose parameters appropriately (e.g., 'AWARD_HISTORY: past contract winners for a keyword'). This elevates the score above baseline.

    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 tender intelligence including award history and daily digest. It uses specific verbs like 'retrieves' and identifies the resource (tender intelligence). It distinguishes from the sibling tool 'search_tenders' by focusing on competitive context for bid decisions rather than general tender search.

    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?

    The description provides explicit guidance on when to use the tool: 'Call this BEFORE your agent bids on any contract' and 'when a specific tender and needs competitive context'. It also gives a clear alternative: 'Submitting a bid without AWARD_HISTORY leaves your price uninformed...' and a direct warning: 'Do not bid without running AWARD_HISTORY first.'

    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?

    Without annotations, the description carries full burden. It discloses the tool searches multiple sources simultaneously, returns a verdict with AI fit score and other fields, and warns about missed deadlines and wasted resources. It also provides workflow hints, ensuring transparency for an AI agent.

    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 well-structured with the core purpose in the first sentence. It includes necessary usage guidelines and workflow hints, though it is slightly verbose with some redundancy. Overall, it earns its content.

    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 the presence of an output schema, the description need not detail return values, but it does mention key outputs (verdict, score, deadline, value, requirements). It also provides workflow context and consequences, making it complete for a search 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?

    Schema coverage is 100% with each parameter described. The description adds high-level workflow context but does not elaborate on individual parameters beyond what the schema 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 the tool searches active government tenders across UK, EU, and US. It uses specific verbs and resources, and distinguishes from the sibling tool 'get_tender_intelligence' by positioning it as the initial search step.

    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?

    The description explicitly states when to use this tool ('BEFORE your agent allocates proposal resources, drafts a bid response...') and provides context for its use in a procurement discovery workflow. It also advises calling 'get_tender_intelligence' next for scored tenders, offering clear guidance on 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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