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ictcontact-mcp

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Server Quality Checklist

67%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: list_campaigns enumerates campaigns, campaign_summary returns aggregate totals, campaign_status gives live state, and campaign_result provides per-call details. No two tools overlap in a way that would cause an agent to select the wrong one.

    Naming Consistency3/5

    All tool names use snake_case and share the 'ictcontact' prefix, but the pattern is mixed: 'list_campaigns' follows verb_noun while the other three are noun_noun (campaign_summary, campaign_status, campaign_result). This is readable but not fully consistent.

    Tool Count5/5

    With 4 tools, the server is tightly scoped to campaign monitoring and reporting. Each tool covers a necessary query type without redundant or bloated surface area.

    Completeness4/5

    The tool set covers the core campaign workflow: discover campaigns, get summary stats, check live status, and drill into individual results. Minor gaps exist (no detailed campaign metadata or broader call-record export), but the primary monitoring use case is well covered.

  • Average 3.8/5 across 4 of 4 tools scored.

    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
    • 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.

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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

  • Behavior3/5

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

    Annotations already carry the safety and openness profile (readOnlyHint=true, openWorldHint=true), lowering the bar. The description adds useful return-content context — the four per-call dimensions — and the optional filter, but it does not disclose edge behavior such as empty results for a nonexistent campaign, ordering, or the accepted call-status values. Adequate but not rich.

    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 compact sentence with the core purpose front-loaded ('Per-call results for a campaign') followed by a dense, information-carrying dimension list. Every word earns its place and nothing is redundant with the schema or annotations.

    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 low-complexity tool (2 params, 1 required, no enums, no nested objects) backed by readOnly/openWorld annotations, the description adequately conveys what the tool returns even without an output schema. The notable gap is that the valid values for the 'call status' filter are undocumented in both the schema and the description, which an agent would need to call the tool correctly with filtering.

    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%, so the baseline is 3. The description mildly reinforces the status parameter's meaning by framing it as a filter on call status, which helps distinguish it from campaign-level status, but it adds no value syntax or valid-value information beyond what the schema's minimal descriptions already provide.

    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?

    The description names a specific resource ('Per-call results for a campaign') and enumerates the data dimensions returned (contact, response, answering-machine detection, DNC). The 'per-call' granularity implicitly differentiates it from the campaign_summary sibling, though it never explicitly disentangles 'call status' filtering from the campaign_status sibling, leaving mild ambiguity.

    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?

    No guidance is given on when to select this tool over the three siblings (ictcontact_campaign_summary, ictcontact_list_campaigns, ictcontact_campaign_status). The only usage hint, 'optionally filtered by call status,' is parameter-level guidance rather than tool-selection guidance. Given the potential overlap with campaign_status and campaign_summary, explicit routing would materially help an agent.

    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=true, so the agent knows this is a safe read operation. The description adds context about the kind of totals returned (answered, failed, human vs machine), but it doesn't disclose any additional behavioral traits like incomplete data or refresh timing. With annotations covering the safety profile, the description adds moderate context, not more.

    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. It leads with the core purpose ('Totals for a campaign'), gives concrete examples, and closes with the optional scoping. No filler words; every element contributes to understanding.

    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 two-parameter read-only tool, the description is mostly complete: it explains the output nature, lists sample fields, and clarifies the optional scoping. The absence of an output schema is somewhat mitigated by the example fields. It could be more explicit that omitting usr_id returns campaign-wide totals, but that is reasonably implied by the word 'Optionally.'

    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% for both parameters, with clear descriptions for campaign_id ('The campaign id') and usr_id ('Optional agent/user id to scope the summary'). The description's 'Optionally scope to one agent/user id' restates the schema's optionality without adding new semantic depth. Baseline 3 applies because the schema already carries the burden.

    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?

    The description clearly states the tool's purpose: providing totals for a campaign, with specific examples ('answered, failed, human vs machine'). It identifies the resource (campaign) and the aggregate nature, which distinguishes it from siblings like ictcontact_list_campaigns or ictcontact_campaign_status. However, it doesn't explicitly name or contrast the siblings, so some inference is required.

    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?

    No explicit guidance is given about when to use this tool versus alternatives. The 'Optionally scope to one agent/user id' hints at a use case but doesn't say 'use this for aggregate totals' or 'use campaign_result for individual records.' The description stops at stating what it does without routing the agent relative to siblings.

    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=true, so the safety profile is covered. The description adds useful context about the live, pollable nature of the status and example values, but it does not describe the response shape, possible additional statuses, or polling expectations in more detail.

    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 short sentences with no filler. It opens with the core purpose, includes a concrete example, and closes with a practical usage directive. Every sentence earns its place.

    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 single-parameter read-only tool with no output schema, the description is largely complete. It explains what the tool does and when to poll it. Minor gaps remain around exact returned values and behavior for edge cases, but these are not critical for a tool of this simplicity.

    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?

    The schema has 100% description coverage for campaign_id, and the description only restates that the ID identifies the campaign. No additional parameter semantics are provided beyond the schema, so the baseline score of 3 is appropriate.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states that the tool retrieves the live status of a campaign by id and gives examples like running or stopped. It is clear about the resource and action, but it does not explicitly differentiate itself from sibling tools such as campaign_summary or campaign_result.

    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 provides clear guidance on when to use the tool: 'Poll this while a campaign runs.' This tells an agent the temporal context for invocation. However, it does not mention when not to use it or which sibling tool should be chosen instead.

    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 and openWorldHint, and the description's 'List' wording is consistent. It adds useful context beyond the annotations by specifying the scope ('outbound campaigns') and the field content ('id and name'), though it does not describe ordering, pagination, or response envelope details.

    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 short sentences with the action and result front-loaded, and the instruction to 'Start here' earns its place as workflow guidance. There is no filler, repetition, or unnecessary detail.

    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 parameterless list tool with readOnly/openWorld annotations, the description adequately covers purpose, scope, returned fields, and how it fits into the workflow. It does not document the exact output schema, but the named fields ('id and name') and the simple nature of the tool make this a minor gap.

    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 zero parameters and 100% schema description coverage, so there is nothing for the description to clarify. The description implies a parameterless call by saying 'List the outbound campaigns', and no ambiguity exists.

    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 uses a specific verb ('List') and identifies both the resource ('outbound campaigns on the ICTContact / ICTDialer server') and the returned fields ('id and name'). The phrase 'Start here to find a campaign id' clearly separates this from the sibling tools, which operate on individual campaigns.

    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 explicitly frames this tool as the entry point for discovering campaign IDs, which implies it should be used before campaign_summary, campaign_status, or campaign_result. It does not explicitly name those alternatives or state when not to use it, but the 'Start here' guidance provides clear context.

    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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