@0n1x/rhinogent

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.2.0
Disambiguation5/5
Each tool targets a distinct function: identity creation vs resolution, reputation reading, mandate checking, fact signing, and counterparty verification. No overlap in purpose or ambiguity.
Naming Consistency4/5
All tools share the 'rhinogent_' prefix and use snake_case, but naming pattern is mixed: some use action verbs (get, mint, sign, verify) while others are nouns (identity, mandate). Still clear and predictable.
Tool Count5/5
With 6 tools, the server covers core agent identity and trust operations without being over- or under-scoped. Each tool serves a clear, necessary purpose.
Completeness4/5
Covers create/read for identity, read for reputation, and verification actions. Minor gaps: no update/delete for identity, no mandate creation or outcome submission tools, but these may be handled externally.
Average 3.7/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 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
Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.
MCP servers without a LICENSE cannot be installed.
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.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description indicates it returns a signed response but does not clarify if this is a read-only operation or if it has side effects, authentication needs, or other behavioral traits.
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 two sentences, front-loaded with the tool's core purpose, and contains no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 3 parameters, no output schema, and no annotations, the description should explain parameters fully and the return format. It mentions a signed result but does not elaborate, leaving the agent without critical usage details.
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 0%. The description adds partial meaning by mentioning 'amount, recipient, scope' but does not map directly to the parameters (agent, action, amount_usdc). It helps a little but significant gaps remain.
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 verb 'Confirm' and the resource 'a proposed action/spend', and specifies the outcome of returning IN_SCOPE/OUT_OF_SCOPE signed. It distinguishes this from sibling verification tools by focusing on spend mandate.
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 use when checking if an action is within the agent's mandate, but it lacks explicit guidance on when to use this tool versus alternatives like rhinogent_verify_counterparty, and does not mention exclusions.
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, the description must carry behavioral disclosure. It states the signing algorithm (Ed25519) and output purpose (hand to counterparty), but omits whether the operation is read-only or modifies state, any permissions needed, or rate limits. Partial transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is a single, clear sentence with no redundancy. It efficiently conveys the core purpose, though could benefit from a brief hint about parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and 3 parameters, the description is too short. It does not describe the return format, prerequisites (e.g., identity setup), or behavior when required parameters are omitted or malformed.
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 coverage is 0%, so description must add meaning. It explains 'fact' with examples but does not elaborate on 'subject' or 'evidence'. Partial semantic help but insufficient for all three parameters.
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 signs a fact with Ed25519, distinguishes facts from opinions, and gives examples (outcome, price, merchant detail). The verb 'get' and resource 'attestation of a verifiable FACT' are specific and differentiate from sibling tools like reputation or identity.
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 when an agent needs a signed, verifiable fact to hand to a counterparty, but does not explicitly state when not to use or compare to alternatives. It lacks counterparties for when to use other tools.
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?
The description states that the tool returns a signed verdict grounded in facts, which gives insight into the output nature. However, it does not disclose whether the tool is idempotent, read-only, or has side effects. Since no annotations exist, this gap 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence without any unnecessary words. Every part is relevant and contributes to understanding the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the tool's simplicity, the description lacks details on parameter semantics, behavioral traits, and explicit usage boundaries. It does not provide enough information for an agent to use the tool correctly without prior knowledge.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not explain the 'domain' parameter beyond what is obvious from the tool's name. With 0% schema coverage, the description should add meaning, but it fails to do so, leaving the agent without guidance on domain format or validation.
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?
Purpose is clearly stated: verify a merchant/domain/counterparty before payment or trust. The description distinguishes this from sibling tools by focusing on verification rather than reputation or identity.
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 usage context: 'BEFORE an agent pays or trusts it.' This tells the agent when to invoke this tool. However, it does not explicitly mention when not to use it or contrast with sibling tools like rhinogent_get_reputation.
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?
Absent annotations, the description carries full burden. It explicitly states 'Keys stay with the agent; this reads the public identity', confirming a read-only, non-destructive operation. However, it does not disclose error handling, prerequisites, or potential auth requirements.
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 extremely concise: two sentences with zero waste. The first sentence states the core function, the second adds key behavioral context. Every word earns its place.
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 one parameter and no output schema, the description lists returned items (callsign, did:pkh, credential) but does not specify their structure or format. For a simple lookup, this is moderately complete but lacks explicit details about the response shape.
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?
With 0% schema description coverage, the description must compensate. It describes the parameter as a 'self-custody Base/EVM address' but does not elaborate on format, validation, or specific allowed values beyond the schema's regex pattern. This adds minimal meaning beyond what the schema already provides.
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 resolves a Base/EVM address into a signed Rhinogent identity, listing specific components (callsign, did:pkh, credential). The phrase 'reads the public identity' distinguishes it from write or mutation tools like rhinogent_mint_identity.
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 explicit when-to-use or when-not-to-use guidance is provided. The description implies usage for identity lookup but fails to contrast with siblings like rhinogent_get_reputation or rhinogent_verify_counterparty, leaving the agent to infer context.
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 are provided, so the description carries the full burden. It explains the reputation is based on verified outcomes and is un-gameable, giving insight into its reliability. However, it does not explicitly state that it is a read-only operation or disclose potential side effects, but given it is a read function, the description is sufficient.
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 two sentences that are concise and front-loaded. The first sentence explains the core function and components, and the second adds value by contextualizing the importance. No unnecessary words.
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?
The description explains what the reputation is but does not specify the return format or structure. With no output schema, the agent may need to infer or discover the response type. This is a minor gap given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'agent' is a required string, and the description does not explicitly define its format or semantics beyond the tool's context. Schema description coverage is 0%, so the description adds minimal value; however, it is implicitly clear that 'agent' refers to the identity whose reputation is being read.
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 reads an agent's reputation, specifying the components (Brier score, stake-weighting, behavioral consistency) and the purpose (establishing trust). This distinguishes it from sibling tools like rhinogent_identity or rhinogent_mandate, as the focus is on reputation assessment.
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 the tool is used when you need to assess trustworthiness, but it does not explicitly state when to use it over alternatives or when not to use it. There is no mention of prerequisites or context, so the guidance is minimal.
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?
Given no annotations, the description explains that key generation is client-side and the tool issues a public signed card. It discloses the return format and action (minting). However, it does not detail potential side effects (e.g., overwriting duplicates) or authorization 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?
Two sentences, front-loaded with the primary action and outputs. Every word adds value; no redundancy or filler.
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?
For a simple single-parameter tool with no output schema, the description covers the core functionality and return values. It lacks error handling or prerequisite details, but these are partially mitigated by the clear purpose.
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 coverage is 0% (description does not explicitly describe the 'address' parameter), but the description adds context by stating 'newly-generated Base address', implying freshness and chain. This partially compensates, but the parameter's exact role and format could be clearer.
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: onboarding a fresh self-custody agent and returning a signed identity card. It specifies the exact outputs (callsign, did:pkh, credential) and distinguishes from sibling tools like 'rhinogent_identity' by emphasizing 'mint' (create new) vs. potential retrieval.
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 new agent onboarding ('fresh self-custody agent') but provides no explicit guidance on when to use this tool versus alternatives like 'rhinogent_identity'. It does not mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![rhinogent-mcp MCP server](https://glama.ai/mcp/servers/dimitrilaouanis-tech/rhinogent-mcp/badges/card.svg)](https://glama.ai/mcp/servers/dimitrilaouanis-tech/rhinogent-mcp)

Score Badge

Copy to your README.md:

[![rhinogent-mcp MCP server](https://glama.ai/mcp/servers/dimitrilaouanis-tech/rhinogent-mcp/badges/score.svg)](https://glama.ai/mcp/servers/dimitrilaouanis-tech/rhinogent-mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/dimitrilaouanis-tech/rhinogent-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server