AGS Extend SDK MCP Server
OfficialServer Quality Checklist
Latest release: v2026.4.0
- Disambiguation5/5
The two tools have clearly distinct purposes: one for searching symbols by query, the other for describing specific symbols by ID. There is no overlap in functionality.
Naming Consistency5/5Both tool names follow a consistent verb_noun pattern with hyphens (describe-symbols, search-symbols), making them predictable and easy to understand.
Tool Count3/5With only 2 tools, the server is minimal but possibly sufficient for a focused SDK exploration workflow. The count is on the low end for a typical API surface, but the tools cover the essential search and describe operations.
Completeness4/5The tools enable a complete workflow of searching for symbols and retrieving their details. The missing aspect could be a dedicated list or browse operation, but search with an empty query effectively serves that purpose. Minor gaps include lacking bulk operations or dependency resolution.
Average 4.2/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 18 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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 carries the full burden. It describes pagination behavior and shows usage patterns, but there is a contradiction with the input schema: the first usage pattern omits the required 'ids' parameter. This omission is misleading and reduces transparency.
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 well-structured with sections and examples, making it easy to follow. However, the inclusion of a usage pattern that contradicts the required parameter reduces conciseness and adds confusion.
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 presence of an output schema, the description does not need to explain return values. The provided workflow and usage patterns are helpful, but the contradiction regarding required parameters leaves the description incomplete and potentially misleading.
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 coverage is 100%, so the baseline is 3. The description adds usage patterns that clarify how parameters interact (e.g., pagination with limit/offset), but it does not add significant meaning beyond what the schema already describes. The contradictory usage pattern reduces clarity.
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 describes multiple symbols with pagination, and provides usage patterns that distinguish it from the sibling tool search-symbols. The workflow integrates the two tools effectively.
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?
The description provides explicit usage patterns and a recommended workflow (search then describe). While it does not explicitly state when not to use the tool, the context is clear and the workflow provides guidance.
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?
Despite no annotations, the description discloses pagination behavior, fuzzy matching, and default values. It doesn't state read-only explicitly but is implied by the context. Leaves some room for more explicit safety cues.
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?
Well-structured with sections and front-loaded purpose. However, the multiple example patterns could be condensed 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?
Covers all key usage aspects: search functionality, pagination, filtering, and workflow integration with sibling tool. Output schema exists, so no need to detail return values.
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, baseline is 3. The description adds numerous concrete examples demonstrating how parameters like query and symbolType behave, and clarifies syntax (e.g., comma-separated queries).
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 'Search for symbols by name, tags, or description with fuzzy matching support,' specifying the verb, resource, and distinguishing from the sibling tool 'describe-symbols'.
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?
Provides explicit usage patterns and a recommended workflow that links this tool to its sibling, showing when to use search and when to use describe. It also implies 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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