TokenHub MCP

by Gravitied

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Each tool targets a distinct operation: discovery, workflow execution, state capture, context retrieval, resource reading, and cost estimation. The only slight potential confusion is between retrieve_context and read_resource, but their descriptions clearly separate broad retrieval from specific resource access.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with snake_case (discover_capabilities, run_workflow, capture_state, retrieve_context, read_resource, estimate_cost). This uniformity makes the tool set predictable and easy to navigate.
Tool Count5/5
With 6 tools, the server is well-scoped for a context and resource management purpose. Each tool serves a clear function without redundancy, fitting comfortably within the ideal 3-15 tool range.
Completeness4/5
The set covers core operations for managing context and resources: discovery, execution, saving, retrieval, reading, and cost estimation. Minor gaps include no explicit update/delete operation for saved states or resources, but these may not be essential given the server's focus.
Average 2.9/5 across 6 of 6 tools scored. Lowest: 1.8/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on May 7, 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.
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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

Behavior1/5
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 only says it returns summaries plus resource links, but it does not disclose potential side effects, whether it executes commands, changes state, or requires permissions. The term 'batch' hints at bulk processing but offers no clarity on behavioral implications.
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 sentence with no filler, front-loading the action ('Batch...'). It is efficiently structured, though the brevity comes at the cost of clarity. Still, as far as conciseness goes, every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the high complexity (24 parameters), no output schema, and no annotations, the one-line description is completely inadequate. It fails to define what a workflow is, how it is specified, what inputs are required, or what the returned summaries and resource links look like.
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?
Schema description coverage is 0%, and the description provides no parameter explanations at all. With 24 parameters and numerous enums (depth, target, evidence, provider, execution, outputShape), an agent has no help understanding what parameters like 'ref', 'args', 'query', or 'budgetTokens' mean. This is a critical gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a verb ('Batch'), a resource ('common developer workflow'), and an output ('summaries plus resource links'), which gives some sense of purpose. However, 'common developer workflow' is vague and doesn't specify what workflow or how it is invoked. It doesn't effectively distinguish from siblings like discover_capabilities or read_resource beyond the generic 'workflow' concept.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives, no prerequisites mentioned, and no exclusions or context provided. The description doesn't help an agent decide between run_workflow and other sibling tools.
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 carries the burden of disclosing behavior. It mentions 'token-budgeted' which hints at output limits, but it doesn't disclose authorization needs, rate limits, whether the tool modifies anything, or how results are returned. This is a significant gap for a tool with many sources and parameters.
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 focused sentence with no fluff or repetition. It is concise and front-loaded, stating the core purpose immediately. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (18 parameters, 10 source types, no annotations, no output schema), the description is severely incomplete. It fails to explain the variety of sources, expected behaviors, return formats, or how to construct valid invocations. This one-sentence description is inadequate for the tool's actual scope.
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 schema has 0% description coverage, and the description adds no information about how parameters like source, url, repo, query, or databaseBase64 should be used. The agent has to rely on parameter names alone, which is insufficient for 18 parameters with unclear relationships (e.g., how provider relates to source or when token is needed).
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 performs retrieval ('retrieval') across multiple resource types ('files, Git state, and web pages'), which conveys the core purpose. However, it doesn't explicitly distinguish from sibling tools like read_resource, and it omits several source types listed in the schema (e.g., github, sqlite, postgres, sentry), so it's not fully specific.
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 when-to-use guidance is provided. The description doesn't explain in which scenarios to prefer this tool over alternatives, nor does it mention any prerequisites or exclusions. The phrase 'token-budgeted' implies a use case but is not explicit enough to count as clear context.
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 the full burden of behavioral disclosure. It implies a write operation ('Store') but does not mention side effects, required permissions, how artifacts are linked, or any return behavior. This is a significant gap for a tool with no annotation support.
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, direct sentence that conveys the core purpose without extraneous words. It is front-loaded with the verb and object, making it easy to parse quickly.
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 the tool's moderate complexity (two optional params, no output schema, no annotations), the description is too brief to be complete. It lacks details on what 'resource-linked artifacts' means, how to use the parameters, and when this tool should be invoked relative to siblings. The minimalism leaves critical gaps for correct usage.
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 input schema has two properties (text, label) with no descriptions, and the schema description coverage is 0%. The description does not explain the meaning or purpose of these parameters, nor does it compensate for the schema's lack of detail. An agent cannot infer how to fill these fields correctly.
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 identifies the action (Store) and the resources (logs, snapshots, state summaries) as resource-linked artifacts. It is specific enough to convey the tool's role, though it does not explicitly contrast with sibling tools like retrieve_context or read_resource.
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. There is no mention of context, prerequisites, or exclusions, leaving the agent to infer usage solely from the terse action statement.
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, the description must carry the full burden of behavioral disclosure. It implies a safe, pre-execution estimation but does not explicitly state whether the tool is read-only, whether it consumes tokens, or what side effects (if any) it has. This is a significant gap for a tool that might be expected to only compute estimates.
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, concise sentence that immediately states the tool's purpose and timing. It is front-loaded 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?
Given the lack of annotations, output schema, and parameter descriptions, the description is incomplete. It does not explain what inputs are needed (especially 'operation'), what the output looks like, or any important behavioral details. A user would need additional information to use the tool correctly.
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?
Schema description coverage is 0%, and the description provides no parameter information. The parameter names 'expectedInputTokens' and 'expectedOutputTokens' are somewhat self-explanatory, but 'operation' is ambiguous and could refer to many things. The description does not compensate for the missing schema descriptions.
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: estimating tool cost and token savings. It uses a specific verb ('estimate') and resource ('tool cost and token savings'), and it includes a temporal context ('before an expensive call') that distinguishes it from sibling tools like run_workflow or read_resource.
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 gives a clear usage context: use before an expensive call. However, it does not explicitly mention when not to use it or name alternatives, though the context is enough to infer its role relative to siblings.
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, the description carries the full burden. It mentions 'progressively read' and modes but does not disclose details about return format, how budgetTokens affects output, whether partial reads have side effects, or any permissions/rate limits. The behavioral traits are only superficially hinted at.
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, concise sentence that front-loads the core purpose and enumerates the main modes. Every word contributes, with no filler or repetition.
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 5 parameters, no output schema, and no annotations, the description is too brief. It omits critical information about how the modes work, what the response contains, how budgetTokens influences behavior, and any prerequisites. The tool is more complex than the description addresses.
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 description coverage is 0%, so the description must compensate. It explains the 'mode' parameter by listing snippet, line range, and full content, and 'line range' loosely implies startLine/endLine. However, it does not clarify 'uri' or 'budgetTokens', leaving most parameters semantically underdefined.
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 function: progressively reading a TokenHub resource. It specifies the resource type (TokenHub resource) and the available methods (snippet, line range, full content), which distinguishes it from sibling tools like discover_capabilities or run_workflow.
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 reading resources, especially large ones, but does not explicitly state when to choose this tool over alternatives or when not to use it. The phrase 'progressively read' suggests incremental reading but lacks explicit guidance on selecting modes or comparing with sibling 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?
No annotations are provided, so the description carries the transparency burden. It states the tool finds compact capabilities without loading full schemas, implying a lightweight, likely read-only operation, but it does not disclose other behavioral traits such as authentication, rate limits, or side effects. The description adds some context but not rich 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?
The description is a single, front-loaded sentence that directly states the tool's purpose and key limitation. Every word earns its place with no superfluous information, making it highly concise and well-structured.
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 discovery tool with two parameters and no output schema, the description gives the core concept but omits practical invocation details like what to use for 'query' or how 'limit' affects results. It is adequate for understanding the tool's high-level function but not fully complete for confident correct usage.
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?
The input schema has a 0% description coverage, and the description does not mention the 'query' or 'limit' parameters at all. While the schema defines 'query' as a required string and 'limit' as an optional integer, the description provides no guidance on how to use them, leaving the agent to infer their meaning from names only.
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 uses the specific verb 'Find' with a clear resource ('compact internal developer capabilities') and adds a distinguishing clause 'without loading their full schemas', which sets it apart from the sibling tools. It clearly communicates what the tool does and its unique value.
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 clearly implies the usage context: when you need to discover internal capabilities quickly and do not need full schema details. While it does not explicitly list alternatives or when-not-to-use, the context is unambiguous and the tool's purpose is distinct from its siblings.
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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