Prospeo MCP Server
OfficialServer Quality Checklist
Latest release: v1.0.3
- Disambiguation5/5
Each tool has a unique purpose: search vs enrich vs account info, and company vs person are clearly separated. No overlap or ambiguity.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern (e.g., enrich_company, search_person, get_account_info), making them predictable and easy to understand.
Tool Count5/55 tools cover the essential operations for a data enrichment API: search and enrich for both companies and persons, plus account status. Well-scoped and not excessive.
Completeness5/5The tool surface provides search and enrichment for the two main entity types (company, person) and account info. No obvious gaps for the stated purpose.
Average 4.6/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 4 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.
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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
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds significant context beyond annotations: cost per match, no charge on failure, and the free_enrichment field to check. Also lists output fields, all consistent with readOnlyHint=true.
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?
Concise, front-loaded with purpose, then identifier requirements and credit policy. No wasted words, each sentence adds useful information.
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?
Covers purpose, inputs, output fields, and cost. Lacks error handling details (e.g., what happens if multiple matches found), but given the annotations and simple parameter set, it is nearly complete.
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?
With 100% schema coverage, the description adds value by specifying parameter precedence (company_website most accurate) and explicitly stating that at least one identifier is needed, a constraint not present in the schema.
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 enriches a company by returning a full profile with specific data fields (headcount, industry, etc.). It differentiates from siblings like enrich_person and search_company by focusing on company enrichment with detailed output, and includes identifier requirements.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 like search_company or enrich_person. While it mentions identifier preferences and credit costs, it lacks comparative context for tool selection.
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?
Describes credit system, when charges apply, and response field free_enrichment. Adds context beyond annotations (readOnlyHint, etc.). No contradiction with annotations; readOnlyHint aligns with read operation.
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?
Succinctly packs purpose, identifier requirements, and billing details. Slightly long but every sentence adds value. Front-loaded with purpose.
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?
Adequately describes return value (full profile with email/mobile, job history, company) and includes free_enrichment field. No output schema, so description compensates reasonably.
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?
Adds meaning beyond schema by explaining the credit cost relationship between enrich_mobile and email, and the free_enrichment check. Schema already covers parameter descriptions, but description adds usage context.
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?
Clearly states the tool enriches a person by returning full profile with verified contact info. Distinguishes from siblings like search_person (which searches) and enrich_company (which enriches companies).
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 specifies required identifiers (linkedin_url, email, person_id, or name+company) and conditions for credit charges. Lacks explicit when-not-to-use or comparison to alternatives, but context is clear.
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?
Annotations already declare readOnlyHint=true. Description adds that it's free and does not consume credits, which is helpful behavioral context beyond annotations. No contradiction.
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, front-loaded with purpose, no wasted words. Highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no parameters or output schema, the description lists what the tool returns, which is sufficient for an agent to understand the tool's output. Complete for its simplicity.
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 exist, so the description has no need to explain them. Baseline 4 for zero parameters.
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 checks account status, listing specific fields like credits, plan, renewal date, and team size. It distinguishes from sibling tools (enrich/search) which operate on different entities.
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?
Description specifies two use cases: verifying API key works and checking remaining quota. It also notes the endpoint is free and does not consume credits, giving clear context. No explicit when-not-to-use, but siblings are clearly different.
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?
Annotations declare readOnlyHint=true and destructiveHint=false. Description adds critical behavioral details: credit cost per page with results, obfuscation of email/mobile with status field, and the need to call enrich_person for full values. No contradiction.
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?
The description is detailed but well-structured, front-loading key info (purpose, pagination, credits). Every sentence adds value, though it could be slightly more compact without losing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Comprehensively covers input, behavior, output schema (via description), pagination, costs, and cross-reference to enrich_person. For a complex tool with many filters and no separate output schema, it is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% via description field. The description adds meaning: explains filter structure, required positive filter, pagination, credit cost, and output details (obfuscated previews with status). Adds value beyond the schema.
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?
Clearly states it searches Prospeo's professional database using typed filters, returns person data with pagination, and distinguishes from sibling tools like search_company and enrich_person.
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?
Provides explicit guidance on filter combination, required positive filter, credit cost, and directs to enrich_person for revealing email/mobile. Could mention not to use for company-only search, but sibling distinction is clear.
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?
Annotations already indicate read-only and non-destructive nature; description adds per-page limits, max pages, credit cost, and result summary detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is a single, well-structured paragraph with front-loaded purpose, no redundant sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complex filter schema and no output schema, description covers usage, constraints, cost, result summary, and directs to enrich_company for more data.
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 description adds context: required include filter, lists common filter names, and states result content, providing value beyond schema.
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 the tool searches Prospeo's company database with filters, distinguishing it from enrich_company and search_person.
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 mentions requirement for at least one positive filter, credit cost per page, and points to enrich_company for full profiles.
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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