Rutherford MCP Server

by chapmanjw

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v3.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose. For example, `activity` shows only in-flight background jobs, while `list_jobs` enumerates all tracked jobs. `consensus`, `debate`, and `delegate` cover three different multi-agent interaction modes, and `review` is a specialized consensus variant. No two tools overlap ambiguously.
Naming Consistency3/5
Tool names are a mix of single-word nouns (`activity`, `consensus`, `delegate`) and verb_noun phrases (`cancel_job`, `list_jobs`, `reload_panels`). While all are readable, there is no uniform pattern, making the naming slightly inconsistent.
Tool Count4/5
With 18 tools, the server covers a broad but coherent domain (background jobs, ACP agent management, panels, roles, analysis). The number feels appropriate for the scope, though slightly above a typical 3-15 range, justifying a 4 rather than a 5.
Completeness4/5
The tool surface covers core workflows: agent discovery (`discover`), health checks (`doctor`), task delegation (`delegate`), planning (`plan`), multi-agent deliberation (`consensus`, `debate`), code review (`review`), job management (`list_jobs`, `job_status`, `job_result`, `cancel_job`, `continue_job`), and configuration (`setup`). Minor gaps exist (e.g., no tool to create/edit roles beyond listing them), but the set is largely complete for its stated purpose.
Average 4.5/5 across 18 of 18 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 1 community issues answered or closed in the last 6 months
- 97 commits in the last 12 weeks
- Last stable release on July 26, 2026
- 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.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
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  ]
}
```
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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

Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It thoroughly explains behavioral traits: safety_mode and trust_workspace requirements, fallback behavior (write/yolo never fall back, allow_model_fallback retries on model failure), persistence options, async vs sync mode, and session resumption. This level of detail fully discloses side effects and constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is lengthy and dense. While it is front-loaded with the purpose, the parameter details are presented as a continuous paragraph without clear separation. It could be more concise by using bullet points or summarizing common patterns. Every sentence is informative, but the structure hinders quick scanning.
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?
Given the complexity of the tool (16 parameters, required schema fields, output schema, advanced features like fallback, async, persistence), the description is highly complete. It covers all parameters, default behaviors, edge cases, and explains the return value for async mode. The presence of an output schema reduces the need to describe return values, but the description still adds context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides extensive semantic meaning for each parameter beyond the bare schema. Given a schema description coverage of 0%, the description compensates by explaining every parameter: cli, model, safety_mode, files, role, effort, fallback, allow_model_fallback, persist, session_id, mode, and more. It also explains defaults and interactions.
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 opening sentence clearly states the tool's function: 'Delegate a task to one ACP agent and return its normalized result.' This provides a specific verb and resource, and the tool's name 'delegate' aligns with this purpose. It is distinct from sibling tools like 'consensus', 'debate', 'analyze', and 'plan'.
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 lacks explicit guidance on when to use this tool versus its siblings. It does not mention alternatives or scenarios where delegation is appropriate versus other tools. The parameter explanations are detailed but do not provide usage 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 provided, so description carries full burden. It discloses the side effects (killing work, tearing down process tree) and behavior for finished jobs. Lacks mention of permissions or auth, but sufficient for a kill operation.
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 concise paragraphs with no superfluous information. The first sentence front-loads essential purpose; the second adds useful detail.
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?
Tool is simple with one param and output schema exists. Description covers return values and error case. Could mention that job_id comes from list_jobs, but overall adequate.
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 has no description for job_id (0% coverage). The description implies job_id identifies the job but does not explicitly state its format or origin, leaving some ambiguity.
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 'cancel' and the resource 'running background job', and specifies the return format. It distinguishes from sibling tools like continue_job (opposite) and job_status (read-only).
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?
It indicates when to use (for running jobs) and that cancelling a finished job is a no-op. However, it does not explicitly mention when not to use or provide direct 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?
With no annotations, the description fully covers behavioral traits: it makes real read-only calls, reports specific statuses, handles npm adapters with install hints, distinguishes 'model_unavailable' as non-broken agent, and describes 'connect_only' behavior. Comprehensive and accurate.
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 front-loaded with the main purpose and is structured logically. While it is somewhat lengthy, every sentence adds value, covering edge cases and alternatives. Could be slightly more concise but not wasteful.
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 covers all essential aspects: purpose, behavior, parameters (partially), differentiation from siblings, special cases (npm adapters), and output format hints. Since an output schema exists, return values need not be explained. No notable omissions for a health-check tool.
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%, so description must compensate. It explains 'agent' (one or all) and 'connect_only' in detail but does not mention 'timeout_s' at all. Partial coverage leaves a gap for one parameter.
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: 'Probe each agent (or one named `agent`) with a real read-only ACP round trip and report conformance.' It uses specific verbs and resources, and differentiates from sibling 'capabilities' by noting it is slower and makes real calls.
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?
Provides clear context for when to use: 'run it to see which of the roster actually drive on this machine.' Also explains the 'connect_only' option for cases where model calls would fail due to auth/entitlement/quota issues. Does not explicitly state when not to use, but implies that 'capabilities' is an alternative for faster checks.
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. It discloses that it returns status and timings, that it does not return heavy results, and that unknown IDs yield JOB_NOT_FOUND. It does not cover permissions or rate limits, but these are less critical for a read-only polling tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with the main purpose, then elaborating on status values and usage flow. No unnecessary words or repetition, every sentence adds 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?
Given the tool has a single parameter, an output schema, and 17 siblings, the description adequately covers usage flow and error condition. It explains the polling pattern with job_result, which is critical. Minor omissions like timeouts or concurrency are acceptable for a status tool.
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?
Only one parameter 'job_id' with 0% schema coverage. The description adds context by stating that an unknown ID returns JOB_NOT_FOUND, which goes beyond the schema's type definition. However, no further details about format or validation are provided, so it meets the minimum requirement.
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 'Report one background job's status and timings' with a specific verb and resource. It distinguishes from siblings like job_result by noting 'no heavy result' and mentioning JOB_NOT_FOUND for unknown IDs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides when to use: 'Poll this, then call job_result once the job is succeeded (or to read the failure of a failed / cancelled job).' Also notes that JOB_NOT_FOUND is returned for unknown IDs, guiding the agent on error handling.
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?
With no annotations provided, the description takes full responsibility for behavioral disclosure. It explains the merging logic across multiple config locations and the error behavior on malformed files (raises PANEL_INVALID). This provides sufficient transparency for a read operation.
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 concise with four front-loaded sentences. Each sentence adds unique value: main action, return type, discovery locations, and error handling. No redundant information.
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?
Given no parameters, no annotations, and an output schema described in the text, the description fully covers the tool's purpose, usage context, behavior, and error conditions. It is complete for a tool of this complexity.
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, so the baseline score is 4. The description does not need to add parameter meaning, and the schema is fully covered.
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 action ('re-read saved panels from disk') and the specific scenario ('after editing a `panels.toon`'). It distinguishes the tool from siblings by being highly specific, and no sibling tool performs a similar operation.
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 for when to use the tool ('after editing a panels.toon'). However, it does not explicitly state when not to use it or mention alternatives, though no direct siblings exist.
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?
With no annotations, the description provides full behavioral transparency: it details the four possible result types (succeeded, failed, cancelled/running, unknown) and notes the envelope matches the sync tool. This is comprehensive.
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?
Three sentences, no fluff. The main purpose is front-loaded, followed by clear case-by-case behavior. Every sentence adds value.
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?
Given the presence of an output schema (context signal indicates it exists), the description adequately covers return values for all states. No missing behavioral details for a retrieval 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?
The only parameter is job_id (string, required). Schema coverage is 0%, but the parameter is self-explanatory. The description adds no extra semantics, but given its triviality, it is sufficient. A higher score would require clarifying format or source.
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 returns a finished background job's result envelope, with explicit differentiation for succeeded, failed, cancelled/running, and unknown job IDs. This distinguishes it from siblings like job_status (polling) and list_jobs.
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 explains when to use (for finished jobs) and advises polling job_status for still-running jobs. It also mentions error cases (unknown id returns JOB_NOT_FOUND). It could be more explicit about when not to use, but the guidance is clear.
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?
Given no annotations, the description fully discloses the output format, ordering, and empty case, providing complete behavioral 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 well-structured, front-loads key info, and every sentence adds value without redundancy.
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?
With no parameters and an output schema present, the description fully explains the output structure, making the tool complete to understand.
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?
No parameters exist, so the description adds no param info, which is appropriate. Baseline for 0 params is 4.
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 shows background jobs in flight with live elapsed time, and distinguishes itself from list_jobs explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It directly contrasts with list_jobs, explaining when to use this tool versus the sibling, making the usage context very clear.
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?
Discloses that it's a light listing (no heavy result), jobs are in-memory, evicted after job_ttl_s, cleared on restart. No annotations provided, so description fully covers 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?
Very concise: two short sentences covering purpose, usage, and behavioral context. No wasted words.
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?
Complete given no parameters and presence of output schema. Describes return fields, ordering, and lifecycle. No gaps.
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?
No parameters in input schema, so baseline is 4. No need for additional parameter information.
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?
Clearly states the tool lists background jobs with specific fields (id, tool, status, summary, timestamps) and ordering (newest first). Distinguishes from siblings like job_result by noting it's a light listing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool (light listing) vs alternatives (use job_result for finished job's result). Also provides context on job lifecycle (eviction after ttl, cleared on restart).
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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