Pica MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a distinct purpose in a clearly defined workflow: listing integrations, fetching platform actions, retrieving action documentation, and executing the action. There is no overlap or ambiguity.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern with snake_case (list_pica_integrations, get_pica_platform_actions, get_pica_action_knowledge, execute_pica_action). The verbs are action-oriented and match the tool's function.
Tool Count5/5With 4 tools, the server is lean but covers the essential steps for discovering and executing actions on third-party platforms. Each tool earns its place; the number is appropriate for the scope.
Completeness5/5The toolset provides a complete workflow: discover available integrations, explore platform actions, get detailed action knowledge, and execute the action. There are no obvious gaps or dead ends for the stated purpose.
Average 4.4/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
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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?
No annotations are provided, so the description bears full responsibility. It implies a read-only operation (get) but does not explicitly state it's non-destructive or discuss error handling (e.g., invalid platform names). It adds useful context about input format but leaves gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences: purpose first, then usage guidance, finally input specificity. No redundant words, efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, yet the description does not explain the return format or structure. It mentions 'shows you what actions are available' but lacks detail. For a simple tool, it's adequate but could be improved.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds meaning beyond the schema by specifying that the platform value should be the kebab-case version from list_pica_integrations, clarifying the source and format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get all available actions for a specific platform', using a specific verb and resource. It distinguishes from siblings by mentioning discovery after list_pica_integrations, which sets it apart from execution or knowledge tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to call after list_pica_integrations and to use the exact kebab-case platform name. This provides clear sequencing and input guidance. It does not explicitly state when not to use or alternatives, but the context is sufficient.
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 provided, so description carries the burden. It discloses critical behavioral constraints: only execute when user intends to execute, not for building. It mentions workflow and caution. However, it lacks details on success/error responses, rate limits, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (3 sentences) and front-loaded with purpose, followed by critical guidance and workflow. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, nested objects), no output schema, and no annotations, the description covers when to use but lacks detail on parameter usage, expected output format, and error handling, leaving some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% description coverage, so baseline is 3. The description does not add significant parameter-specific details beyond the schema; it focuses on tool usage rather than parameter meanings.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Execute a Pica action to perform actual operations on third-party platforms.' It further distinguishes from sibling tools by specifying the required workflow and contrasting with build/create scenarios.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance on when to call (user intent to execute) and when not to call (user wants to build/create). Includes required workflow: must call get_pica_action_knowledge first, and ask for confirmation if uncertain.
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 provided, but description accurately conveys it's a read operation that loads documentation into context. It does not disclose any side effects, but given the read-only nature, this is sufficiently transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is front-loaded with purpose, followed by mandatory usage instruction. Each sentence adds value, though could be slightly more concise. No fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description states it provides 'comprehensive documentation' which sufficiently covers return value. For a 2-param tool with no nested objects, the description is complete enough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%. The description adds value by explaining that action_id comes from get_pica_platform_actions and platform is kebab-case from list_pica_integrations, providing integration context beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get comprehensive documentation for a specific action', using a specific verb and resource. It distinguishes from siblings (execute, list actions, list integrations) by focusing on documentation retrieval and mandatory pre-execution role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs 'You MUST call this tool before execute_pica_action' and states it is required before create_pica_request, providing clear when-to-use guidance and rationale.
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 provided, so description carries full burden. It discloses return format (kebab-case platform names) and mentions it returns connections. Could be more detailed about what 'connections' entail, but adequate for a read-only list operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no fluff. Essential information front-loaded with key instruction first, then detail on output format and purpose. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, description adequately explains what is returned and its format. Provides context on why this tool is necessary for other tools. Loses a point for not specifying whether the output includes metadata beyond names, but still sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters, schema coverage 100%. Description adds value by explaining the return format and usage of the output (platform names in kebab-case), which is helpful for subsequent tool invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'List all available Pica integrations and platforms' with a specific verb and resource. It distinguishes itself from siblings (execute_pica_action, get_pica_action_knowledge, get_pica_platform_actions) by being the initial discovery tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'ALWAYS call this tool first in any workflow' and explains why (to discover platforms and connections needed for subsequent calls). Provides clear context for when to use vs 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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