Trade Surveillance Support MCP Server

by vic3custodio

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap. The tools cover different stages of a workflow: parse_email_inquiry for input analysis, search_sql_configs/search_java_code for resource discovery, execute_java_report for execution, generate_response_summary for output formatting, and rebuild_metadata_index for maintenance. An agent can easily distinguish between them based on their specific functions.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with snake_case naming. The verbs are clear and descriptive (execute, generate, parse, rebuild, search), and the nouns precisely indicate the target resource or action. There are no deviations in naming conventions across the six tools.
Tool Count5/5
Six tools is well-scoped for a trade surveillance support server. Each tool serves a distinct purpose in the workflow, from inquiry parsing to report generation and response formatting. The count is neither too thin nor bloated, providing comprehensive coverage without redundancy.
Completeness4/5
The toolset covers the core trade surveillance workflow effectively: parsing inquiries, searching for relevant configurations and code, executing reports, and generating responses. A minor gap exists in direct data manipulation or validation tools (e.g., validate_trade_data, update_config), but agents can work around this using the existing search and execution tools. The surface supports end-to-end processing without dead ends.
Average 4.1/5 across 6 of 6 tools scored. Lowest: 3.1/5.
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
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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

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 behavioral disclosure. It describes the tool's function but lacks critical behavioral details: it doesn't mention whether this is a read-only or mutating operation, what permissions might be required, error handling, or performance characteristics. The description is functional but insufficient for a tool with complex inputs and output.
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 and appropriately sized: a purpose statement, elaboration, parameter details, and return value—all in a compact format. It's front-loaded with the core function. Minor verbosity in the elaboration sentence could be tightened, but overall it earns its place efficiently.
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 complexity (3 parameters with nested objects, no annotations, but with an output schema), the description is moderately complete. It covers parameters and return value at a high level, and the output schema handles return details. However, it lacks behavioral context and usage guidelines, leaving gaps for safe and effective tool invocation.
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 description coverage is 0%, so the description must compensate. It provides a clear 'Args' section that names and briefly describes all three parameters ('parsed_email', 'config_files', 'report_path'), adding meaningful context beyond the bare schema. However, it doesn't detail expected formats or constraints (e.g., what 'parsed_email' structure entails).
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: 'Generate a summary response for the user inquiry with all relevant information' and 'combines all the gathered information into a clear, actionable response'. It specifies the verb ('generate', 'combines') and resource ('summary response'), though it doesn't explicitly differentiate from sibling tools like 'execute_java_report' or 'parse_email_inquiry'.
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?
The description provides no guidance on when to use this tool versus alternatives. It mentions combining 'gathered information' but doesn't specify prerequisites, timing relative to other tools (e.g., after 'parse_email_inquiry'), or exclusions. This leaves the agent without context for tool selection among 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the tool as executing a unit test to generate a report, implying it performs a read/write operation (since it saves output) and validates execution. However, it lacks details on permissions, error handling, rate limits, or side effects. The description adds some context but is incomplete for a tool with mutation capabilities.
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 purpose statement, explanatory paragraph, and separate Args and Returns sections. It is appropriately sized and front-loaded, with no redundant sentences. Minor improvements could include tighter phrasing, but overall it is efficient and organized.
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?
Given the tool's complexity (3 parameters, no annotations, but has an output schema), the description is reasonably complete. It explains the purpose, parameters, and return value, and the output schema handles return details. However, for a tool that executes tests and generates reports, more behavioral context (e.g., execution environment, error modes) would enhance completeness.
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 schema description coverage is 0%, so the description must compensate. It provides a dedicated 'Args' section explaining each parameter's purpose (e.g., 'fully qualified Java class name,' 'Path to the SQL config file,' 'Directory where the report should be saved'), adding meaningful semantics beyond the bare schema. However, it does not specify formats or constraints for the config_file path or output_directory beyond examples.
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's purpose: 'Execute a Java unit test to generate a trade surveillance report.' It specifies the verb ('execute'), resource ('Java unit test'), and outcome ('generate a trade surveillance report'), distinguishing it from sibling tools like search_java_code or search_sql_configs. The first sentence provides a complete and specific purpose statement.
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 usage context by mentioning 'trade surveillance report' and 'validated during execution,' but it does not explicitly state when to use this tool versus alternatives like search_java_code or generate_response_summary. There is no guidance on prerequisites, exclusions, or comparisons to sibling tools, leaving the agent to infer appropriate usage scenarios.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes what the tool does (analyzes email content to extract specific information) and outlines the return structure, though it lacks details on error handling, performance limits, or authentication needs.
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 appropriately sized and front-loaded, starting with a clear purpose statement followed by bullet points of extracted information and a concise specification of arguments and returns. Every sentence adds value without 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?
Given the tool's moderate complexity (1 parameter, no annotations, but with an output schema), the description is largely complete: it explains the purpose, parameter semantics, and return values. The output schema reduces the need to detail return structure, though additional context like error cases or limitations could enhance completeness.
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 description coverage is 0%, so the description must compensate. It adds meaning by specifying that 'email_content' is 'the full text content of the user's inquiry email', clarifying the parameter's purpose beyond the schema's basic type and title. However, it does not detail format constraints or examples.
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's purpose with a specific verb ('parse') and resource ('user inquiry email'), and distinguishes it from sibling tools by focusing on email analysis rather than report execution, summary generation, metadata rebuilding, or code/config searching.
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 usage context ('for investigation') but does not explicitly state when to use this tool versus alternatives. No exclusions or prerequisites are mentioned, leaving the agent to infer appropriate scenarios based on the purpose alone.
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 discloses that the tool searches 'indexed Java files' and uses 'javadoc metadata annotations', adding context about the search mechanism. However, it lacks details on behavioral traits such as performance (e.g., speed, limitations), error handling, or prerequisites (e.g., need for pre-indexed files), leaving gaps in 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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by explanatory details and a structured format with 'Args' and 'Returns' sections. Every sentence adds value, such as the javadoc example and parameter explanations, with no redundant information.
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?
Given the tool's moderate complexity (2 parameters, no annotations, but with an output schema), the description is mostly complete. It covers purpose, usage context, parameter semantics, and return value overview. The output schema exists, so detailed return explanations are not needed, but it could improve by addressing behavioral aspects like indexing requirements or error cases.
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 description coverage is 0%, so the description must compensate. It adds meaning by explaining 'search_keywords' with examples (e.g., 'report generator') and clarifies that 'code_directory' is 'used for initial scan', providing context beyond the schema's basic titles. However, it does not detail parameter constraints or formats (e.g., keyword syntax, directory validity), partially compensating for the low 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?
The description clearly states the specific action ('search for Java classes') and the unique mechanism ('using metadata keywords instead of file paths'), distinguishing it from potential file-based search tools. It explicitly mentions the resource (Java classes) and the method (javadoc metadata annotations), making the purpose unambiguous and distinct from siblings like 'search_sql_configs'.
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 context on when to use this tool: for searching Java classes via metadata keywords rather than file paths. It implies usage for indexed Java files with javadoc metadata, but does not explicitly state when not to use it or name alternatives among siblings like 'rebuild_metadata_index' for indexing tasks.
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?
With no annotations provided, the description carries full burden and does well by explaining the search mechanism (indexed files, metadata annotations), providing concrete examples of metadata format, and describing the return format. It doesn't mention performance characteristics, rate limits, or authentication needs, but covers the core behavior adequately.
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 efficiently structured with a clear purpose statement, usage explanation, metadata examples, and separate Args/Returns sections. Every sentence adds value, and information is well-organized without redundancy.
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 tool's moderate complexity, no annotations, but with output schema present, the description provides complete context: clear purpose, usage guidance, behavioral details, parameter explanations, and return format description. The output schema handles return structure, so the description focuses appropriately on operational context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by explaining both parameters: 'search_keywords' gets examples and context about metadata matching, and 'config_directory' explains its purpose ('used for initial scan') with a default value. The description adds significant meaning beyond the bare 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 the tool's purpose with specific verb ('search') and resource ('SQL configuration files'), and distinguishes it from path-based searches by emphasizing metadata keyword searching. It explicitly differentiates from potential sibling tools by focusing on SQL config files rather than Java code or other resources.
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 context about when to use this tool ('using metadata keywords instead of file paths') and includes examples of metadata annotations. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the sibling tools, though the distinction from path-based searching is implied.
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?
With no annotations provided, the description carries full burden and does well by explaining the tool's purpose, triggering conditions, and automatic vs manual behavior. It doesn't mention performance implications, error handling, or permissions, but provides solid operational context.
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?
Perfectly structured with purpose statement, usage guidelines, and parameter explanations in separate logical sections. Every sentence earns its place with no wasted words, and key information is front-loaded.
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 tool's complexity (rebuilding indexes across file systems), no annotations, and the presence of an output schema (handling return values), the description provides complete operational context including purpose, when to use, parameter meanings, and return value summary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by clearly explaining both parameters (config_directory for SQL config files, code_directory for Java source files) and their purposes, adding essential meaning beyond the bare 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 the specific action ('rebuild the metadata index') and resources involved ('scanning all SQL configs and Java files'), distinguishing it from sibling tools like search_java_code or search_sql_configs which only search rather than rebuild indexes.
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?
Explicit guidance is provided on when to use this tool ('when you've added new files or updated metadata annotations') and when not to use it ('automatically built on first search'), with clear context about manual vs automatic rebuilding.
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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