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shanejonas

openrpc-mpc-server

by shanejonas
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: rpc_call is for executing arbitrary JSON-RPC methods, while rpc_discover is specifically for server discovery to list available methods. There is no overlap in functionality, making them easy to distinguish.

    Naming Consistency5/5

    Both tools follow a consistent 'rpc_' prefix pattern with descriptive suffixes (call, discover), using snake_case throughout. This provides a predictable and readable naming convention across the tool set.

    Tool Count3/5

    With only 2 tools, the server feels minimal but appropriate for its narrow scope of JSON-RPC interaction. However, it lacks tools for common operations like server health checks or parameter validation, which could enhance usability in this domain.

    Completeness3/5

    The tools cover the core actions of calling methods and discovering server capabilities, which aligns with the OpenRPC domain. However, there are notable gaps such as error handling tools, batch request support, or schema validation that would provide more comprehensive coverage for JSON-RPC workflows.

  • Average 3.1/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • 0 of 1 issues responded to 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

  • 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.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
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  ]
}

    Then . Browse examples.

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Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

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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 states the tool performs a JSON-RPC call but lacks details on error handling, authentication needs, rate limits, or what the response might look like. The example prompt format adds minimal context but doesn't cover key 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.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is appropriately concise with two sentences: one stating the purpose and one providing an example prompt. The structure is front-loaded with the core functionality, though the example could be slightly more informative.

    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?

    For a tool that performs potentially complex remote procedure calls with no annotations and no output schema, the description is insufficient. It lacks details on error cases, response formats, authentication, or how to handle the stringified parameters, leaving significant gaps in understanding the tool's behavior.

    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 100%, so the schema already documents all three parameters. The description adds minimal value by mentioning parameters in the example prompt but doesn't provide additional semantics beyond what the schema provides, such as format expectations or usage examples for the 'params' string.

    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: 'Call any JSON-RPC method on a server with parameters.' It specifies the verb ('Call'), resource ('JSON-RPC method'), and scope ('on a server'), though it doesn't explicitly differentiate from the sibling tool 'rpc_discover' beyond the example prompt format.

    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 like 'rpc_discover'. It only gives an example user prompt format without explaining the context, prerequisites, or exclusions for using this tool.

    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?

    With no annotations provided, the description carries full burden for behavioral disclosure. While it mentions this is for discovery and references the OpenRPC Specification, it doesn't describe what the tool actually returns (method list, schema, etc.), error conditions, authentication requirements, or rate limits. The example prompt helps but doesn't fully explain behavior.

    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 appropriately sized with two sentences. The first sentence states the technical implementation, and the second provides a helpful usage example. Both sentences earn their place, though the structure could be slightly more front-loaded with the core 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?

    For a tool with no annotations and no output schema, the description should do more to explain what the tool returns. While it mentions discovery, it doesn't describe the response format, whether it returns method names, schemas, or other metadata. The example prompt helps but doesn't fully address output expectations.

    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 100%, so the schema already documents the single 'server' parameter as a URL. The description adds marginal value by implying this parameter should be a JSON-RPC server URL in the example, but doesn't provide additional format requirements or constraints beyond what's in 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?

    The description clearly states the tool uses JSON-RPC to call `rpc.discover` for server method discovery, which is a specific verb+resource combination. However, it doesn't explicitly distinguish this from its sibling tool `rpc_call`, which would handle actual RPC method calls rather than discovery.

    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 with the example prompt 'What JSON-RPC methods does this server have? <server url>', indicating when to use this tool. It doesn't explicitly state when NOT to use it or mention the alternative `rpc_call` tool, but the context strongly implies this is for discovery rather than execution.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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