@gblin-protocol/mcp-server
Server Quality Checklist
Latest release: v1.1.4
- Disambiguation5/5
Each tool targets a distinct function: treasury health analysis, governance state, treasury state, investment calldata, swap preview, and swap calldata. No functional overlap.
Naming Consistency4/5All tool names follow a verb_noun pattern in snake_case, with some including prepositions or suffixes like 'jit'. The pattern is consistent enough for an agent to predict naming.
Tool Count5/5Six tools cover the essential operations for the GBLIN protocol: reading health, governance, and treasury state, plus generating calldata for investment and swaps. The count is well-scoped.
Completeness4/5The set covers read and write operations for the core treasury and swap functionality. Missing a governance write tool, but the read-only governance state is present. Minor gap.
Average 4.4/5 across 6 of 6 tools scored. Lowest: 3.8/5.
See the Tool Scores section below for per-tool breakdowns.
- 2 of 4 community issues answered or closed in the last 6 months
- 73 commits 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.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
This server has been verified by its author.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
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?
With no annotations, the description carries full burden. It discloses calldata generation, atomicity, and wallet compatibility, but omits behavioral details like prerequisites (e.g., GBLIN balance, approvals) or cooldown implications.
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 key 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.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter tool with no output schema, the description covers purpose, usage timing, and compatibility. However, it could briefly mention the return format (calldata hex) and prerequisites for a more complete picture.
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% with basic descriptions for both parameters. The description adds no additional detail beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates calldata for converting GBLIN to USDC via a specific function. However, it does not explicitly distinguish from siblings like invest_usdc_to_gblin or quote_safe_swap, missing a clear differentiation.
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 guidance on when to use ('immediately before paying an x402 invoice') and notes wallet compatibility, but lacks when-not-to-use or alternative tool references.
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 provided, so description carries full burden. Discloses analysis scope and optional computation, but does not explicitly state that the tool is read-only or has no side effects. Adequate but could be more precise.
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 concise sentences, front-loaded with key purpose, specific metrics, and actionable context. No redundant or unnecessary words.
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 main outputs (balances, gas, runway, recommendation) despite no output schema. Lacks detail on return format or error handling, but sufficient for a single-function analysis tool.
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 covers parameters 100% with descriptions. Description adds value by explaining that daily_burn_usd enables days of runway and rebalance recommendation, beyond schema details.
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?
Clear verb 'Analyze' and specific resource 'agent wallet's treasury health'. Lists exact metrics (GBLIN/USDC/ETH balances, gas runway, days of runway, rebalance recommendation), distinguishing it from sibling tools like get_treasury_state or swap 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?
States 'Critical for autonomous decision-making,' implying when to use. Does not explicitly exclude scenarios or name alternatives, but sibling context (analysis vs. actions) provides clarity.
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 declares 'Read-only', disclosing key behavioral trait. Lists exact data points inspected and optional status reporting. Could add more on side effects or permissions but sufficient for a read-only tool.
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 precise sentences front-load the purpose and constraints. No filler, every phrase earns its place.
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 one optional parameter and no output schema, the description fully covers expected behavior and return semantics, listing all governance aspects checked.
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 value by explaining the optional parameter's purpose: 'reports the status of that specific timelock operation', going beyond the schema's label.
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 uses specific verbs and resources: 'verify GBLIN protocol governance state', and enumerates concrete checks (ownership, delays, role counts, pending proposals). It clearly distinguishes from siblings like 'analyze_treasury_health' by focusing on governance, not treasury.
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 states 'use this to gate trust-sensitive agent actions', providing clear context. Doesn't name alternative tools for governance but implies this is the go-to readiness check.
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?
No annotations are provided, so the description fully carries the burden. It discloses read-only nature, dynamic slippage buffer details (2.5% normal / 4% during Crash Shield), and return elements (expected output, minOut, fee breakdown).
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 a single concise sentence packed with essential information, no unnecessary words.
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?
For a simple 2-parameter tool with no output schema, the description adequately explains inputs, outputs, and behavior (read-only, slippage buffer). No gaps given the tool's simplicity.
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 description coverage is 50% (only amount_in has a description). The description adds no further explanation beyond what the schema provides; for instance, the direction enum values are not elaborated. Baseline 3 due to partial coverage.
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 it previews a buy or sell without executing, specifying the exact tokens (ETH/GBLIN) and what it returns, distinguishing it from actual swap 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?
It explicitly states 'without executing,' indicating it is for previewing. However, it does not explicitly contrast with sibling swap tools or provide when-not conditions.
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. 'Read' implies read-only, but does not explicitly state no side effects or auth. Reasonably transparent for a simple read.
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: first tells what data is returned, second gives usage guidance. No wasted words, front-loaded.
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?
No output schema, but description enumerates return values (NAV, basket composition, weights, Crash Shield status). Sufficient for a simple read tool among siblings.
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 (0), schema coverage 100%. Description does not need parameter details. Baseline score appropriate.
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 verb 'Read' and resource 'GBLIN protocol state'. Specifies exact data returned: NAV, basket composition with dynamic weights, Crash Shield status. Distinguishes from siblings as a read-only observation 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 instructs 'Use this BEFORE any swap to know the current price and risk regime.' Provides clear context for when to use versus alternatives.
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?
No annotations are provided, so the description fully carries the burden. It discloses that the tool generates calldata (not executes), returns two sequential steps, and includes MEV protection via minOut values that never accept 0.
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 sentences with clear, front-loaded information. Every sentence serves a purpose: purpose, steps, and security. No wasted words.
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 one parameter and no output schema, the description fully explains what the tool returns (two steps) and includes critical security context, making it complete for an agent to invoke correctly.
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?
The single parameter usdc_amount has a schema description covering 100%. The description adds context about decimal string and automated minOut handling, providing marginal added 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?
The description clearly states the verb 'Generate calldata' and the resource 'USDC into GBLIN', distinguishing it from siblings like swap_gblin_to_usdc_jit (reverse) and quote_safe_swap (quote vs calldata).
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 implies usage for converting USDC earnings to GBLIN for treasury accumulation, but does not explicitly exclude alternative tools or state when not to use it. However, sibling context provides differentiation.
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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