@gryps/agent-mcp

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by gryps-finance

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v0.2.0
Disambiguation5/5
Each tool targets a distinct aspect of the Gryps venue: funding parameters, market details, market listing, open interest, liveness, and quirks. There is no overlap between them, making tool selection unambiguous.
Naming Consistency4/5
All tool names use snake_case and prefix 'gryps_'. Most follow a verb_noun pattern (e.g., gryps_get_funding, gryps_list_markets), but gryps_open_interest lacks an explicit action verb, creating a minor inconsistency.
Tool Count5/5
With six tools, the set is well-scoped for an MCP server focused on venue data. Each tool serves a clear purpose without redundancy, and the count is neither too small nor too large.
Completeness4/5
The tools cover key read operations for a venue (listing, details, funding, open interest, liveness, quirks). While missing potentially useful endpoints (e.g., historical data or trades), the set feels complete for its informational focus.
Average 3.7/5 across 6 of 6 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
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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?
No annotations provided, so description bears full burden. It states what data is returned but does not disclose any behavioral traits such as read-only nature, potential side effects, authorization requirements, or rate limits.
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 a single 11-word sentence that front-loads the key purpose and specific fields. No extraneous text.
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 simplicity (1 parameter, no output schema, no annotations), the description is minimally adequate. It names the returned fields but lacks details on output format or parameter semantics. The absence of output schema means the agent cannot infer return structure beyond the brief field list.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 1 parameter (symbol) with 0% description coverage in schema. Description does not explain the parameter's meaning or usage, only implying it identifies the market. The description adds minimal value beyond the schema.
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?
Description clearly states the tool retrieves funding parameters for a Gryps market, mentioning specific fields (epoch duration, max rate). It distinguishes from siblings like gryps_get_market which likely returns market details. However, the description lacks an explicit verb but the tool name includes 'get'.
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?
No guidance on when to use this tool versus alternatives. The description does not mention when not to use it or provide context about which sibling tools cover different use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are supplied, and the description does not disclose behavioral traits such as side effects, idempotency, or authentication requirements. It implies a read operation but never explicitly confirms this, which is a gap given the lack of annotations.
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 a single, well-structured sentence that conveys the purpose and key details without unnecessary verbosity. It front-loads the core concept and uses examples 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?
For a simple tool with two optional parameters and no output schema, the description covers the basic purpose and filtering capabilities. However, it does not describe the response format or any pagination/ordering, leaving some gaps in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50%, with venueId having an example in the schema and severity being an enum. The description adds the concept of filtering but does not elaborate on parameter format or constraints beyond what the schema provides. Per the rubric, a baseline of 3 is appropriate given the moderate coverage.
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 it is a registry of dated, verified operational quirks with machine-actionable agent rules, and mentions filtering by venue and severity. This distinguishes it from sibling tools like venue_liveness or funding. However, it does not explicitly state the action (e.g., 'query' or 'retrieve'), slightly reducing clarity.
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?
No guidance is provided on when to use this tool versus alternatives such as gryps_venue_liveness or gryps_get_funding. The description only states filtering options, leaving the agent to infer appropriate contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It mentions 'raw upstream shape' and 'timestamped' but does not clarify if the operation is read-only, requires authentication, or has side effects. More detail on the nature of the query (e.g., is it cached? real-time?) would improve 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 a single, efficient sentence that conveys the tool's purpose and key characteristics. It is front-loaded with the most important information and contains no filler.
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 lack of output schema and low complexity (0 parameters), the description is fairly complete but lacks detail on the exact return format. 'Raw upstream shape' is vague; stating the structure or fields would improve 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?
There are zero parameters and the empty schema is fully covered. The description adds value by describing the output as 'aggregated', 'raw upstream shape', and 'timestamped', which provides context beyond the schema. Baseline is 4 for no parameters, and the description justifies it.
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 it provides an 'aggregated open interest snapshot' for the venue, specifying 'raw upstream shape' and 'timestamped'. This distinctively separates it from sibling tools like gryps_get_funding (funding rates) and gryps_get_market (market data).
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?
While the tool's name and description imply it's for open interest data, there is no explicit guidance on when to use it versus alternatives, nor any prerequisites or exclusions. The sibling names provide some context but the description itself lacks usage directives.
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. Description lists return fields but does not explicitly state read-only nature, permissions, or side effects. For a 'get' operation, it's adequate but not fully transparent.
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?
Single sentence that efficiently conveys purpose and key return fields. No wasted words, front-loaded with value.
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?
No output schema, but description lists return fields explicitly. Covers main aspects of a single-market detail tool. Could include more on response format or size, but sufficient for the agent to understand what to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
100% schema coverage. Description provides examples for symbol parameter (BTC, XAU, SEIUSDT), same as schema description. Adds no new meaning beyond schema, baseline 3.
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?
Clear verb and resource: get full detail for one Gryps market. Lists specific fields (leverage, notional bounds, fee schedule, funding epoch, categories), distinguishing it from siblings like gryps_list_markets (list all) and gryps_get_funding (funding specific).
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?
Implies use when needing full market details, but no explicit when-to-use or when-not. No mention of alternatives like gryps_list_markets for overview or gryps_open_interest for interest data.
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. The description mentions that fees and leverage are live venue data, but does not disclose other behavioral traits like rate limits, data freshness guarantees, or authentication requirements. The description is neutral but lacks detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states the core purpose, second adds filtering and data nature. No unnecessary words. Front-loaded and efficient.
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?
Adequate for a list tool with no output schema. Missing details on pagination (how limit works, default), sorting, and response structure. With no annotations, more behavioral context would be helpful.
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 67% (rfqOnly and category have descriptions, limit does not). The description adds value by giving examples for category ('Commodities', 'Stocks', 'RWA') and indicating that fees/leverage are live data. This supplements the schema well.
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 it lists live Gryps markets, with filtering options. It distinguishes from siblings like gryps_get_market (single market) and gryps_venue_liveness (venue status), so purpose is specific and differentiated.
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 for listing markets with filters, but does not explicitly state when to use this tool versus alternatives like gryps_get_market or gryps_venue_liveness. No exclusion criteria or when-not-to-use guidance is provided.
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 provided, so description carries full burden. It reveals key behavioral details: returns specific data (state root, sequence number, custody, implementation), functions as a chain-side source of truth, and works independently of API status. No contradictions.
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?
Two sentences, no wasted words. First sentence lists key data points and context; second sentence adds crucial usage advantage. Efficiently 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?
The description fully covers what the tool returns and when to use it. With no output schema, the description serves as the sole documentation for return values, which it provides clearly. Adequate for a simple, stateless read tool.
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?
Tool has zero parameters, so schema coverage is 100%. The description does not need to add parameter info. Baseline for zero params is 4, and no additional context is required.
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: a chain-side venue heartbeat providing state root, sequence number, USDC custody, and current implementation. It differentiates from sibling tools which focus on funding, markets, open interest, and quirks.
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 explicitly highlights when to use this tool: even when the venue API is down, as the chain is the truth source. It implies reliability checks over API-dependent data, though it doesn't explicitly list exclusions or alternative tools.
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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