Verified business OSS MCP for search, RSS, crawling, documents, browser, media and transcription.
Scored across 5 tools
The five tools have mostly distinct purposes: business tool recommendations, GitHub job generation, stack listing, RSS fetching, and web search. There is minor overlap between business_tool_routes and list_stack, as both deal with tool stacks, but they target different audiences and outputs.
Naming is inconsistent. Tools like rsshub_fetch and searxng_search follow a verb_noun pattern, while business_tool_routes and github_job_template are noun phrases. list_stack is a verb_noun but the rest do not follow a uniform convention, making the API surface less predictable.
With exactly 5 tools, the server sits comfortably within the typical 3-15 range. Each tool provides a distinct capability without unnecessary bloat or excessive fragmentation.
The domain is a mix of unrelated functionalities (business recommendations, GitHub actions, web search, RSS). While each tool covers its stated purpose, the lack of a cohesive domain makes it hard to assess whether any operations are missing. For example, there is no tool for managing or updating GitHub jobs beyond generating a template, and no explicit search for business or stack data beyond the provided routes.
Return the recommended OSS tool chain for each business.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds a minor behavioral hint that results are per business, but it does not disclose the output format, pagination, or any other operational traits. With annotations present, this meets the baseline but adds limited extra context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no filler. The verb and resource are front-loaded, and every word contributes meaning. It is appropriately minimal for a tool with no parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with no parameters and no output schema, the description is mostly adequate. It clearly states what is returned, but it lacks detail on the exact structure (e.g., list vs. map) and any caveats. Given the simplicity, it is sufficient but could be slightly more explicit about the output format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema is trivially 100% covered. Per the rubric, 0 params yields a baseline of 4. The description correctly avoids any parameter explanations since none exist.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Return') and resource ('recommended OSS tool chain') with clear scope ('for each business'). It clearly distinguishes from sibling tools like github_job_template, list_stack, rsshub_fetch, and searxng_search, which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. The description does not mention any conditions, exclusions, or comparative contexts. The agent is left to infer usage solely from the tool name and sibling names, which is insufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Generate the exact GitHub Actions job JSON for a heavy OSS worker accessible through the connected GitHub account.
| Name | Required | Description | Default |
|---|---|---|---|
| tool | Yes | ||
| input | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description's 'Generate' is consistent with readOnlyHint and idempotentHint since producing a JSON payload is side-effect-free. It adds no extra behavioral details beyond annotations, such as whether network calls are made or how the GitHub account is used. Annotations already cover the key safety aspects, so this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no redundant words and clearly states the output format (JSON). It loses a point because the ambiguous 'heavy OSS worker' phrase and the lack of any structural hint about the 'input' object slightly hurt clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description provides the core purpose but omits essential details: what 'input' should contain, how 'tool' maps to a job, whether the result is a full workflow file, and any constraints on the input object. With no output schema, these gaps cannot be filled elsewhere.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not explain what 'tool' and 'input' mean or how they affect the generated job. With 0% schema description coverage, the agent must guess that 'tool' selects one of the listed tools and that 'input' is a configuration object. This is a major gap because the 'input' field is an arbitrary object with no explanation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool generates GitHub Actions job JSON for a worker using a specified tool, which is a clear verb and resource. However, 'heavy OSS worker' is ambiguous—possibly meaning a headless/resource-heavy workload—and it doesn't clarify how the enum of tools relates to the generated job. It distinguishes from siblings only implicitly as a template generator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives like list_stack or searxng_search. It doesn't mention use cases, prerequisites, or conditions. The phrase 'accessible through the connected GitHub account' hints at context but isn't a usable usage guide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List the 15 open-source tools and how ChatGPT should route each capability.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, and the description's 'list' implies read-only behavior. No contradiction, but the description adds little beyond what annotations already convey.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One direct sentence with no unnecessary detail or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While it states the purpose, it does not specify the output format or what 'route each capability' means in detail, which may leave some ambiguity for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has no parameters, so coverage is effectively 100%. There is nothing for the description to add about parameters, and the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the verb 'list' and the specific resource 'business OSS stack', and mentions the unique aspect of routing capabilities. The topic distinguishes it from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides no guidance on when to use this tool versus the sibling tools, so agents must infer the appropriate context from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch an RSSHub route using a failover pool of public RSSHub instances.
| Name | Required | Description | Default |
|---|---|---|---|
| route | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds the failover pool behavior, which is useful context beyond annotations, but it does not disclose response format, error behavior, or rate limits. With annotations handling the safety profile, the description provides modest additional value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no filler, front-loading the core action and the failover mechanism. Every word adds value, and it is appropriately short for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool, the description covers the core operation and failover, but it omits critical details: how to construct the route parameter and what the response looks like. Without an output schema, the description should at least hint at the return type (e.g., RSS/XML or JSON). This is a noticeable gap for an agent to call it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 for the undocumented 'route' parameter. However, the description only mentions 'route' without specifying its format, examples, or whether it expects a full URL or just a path. This leaves the agent guessing what to pass, which is a significant gap for a tool with only one parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches an RSSHub route using a failover pool of public instances. This is a specific verb and resource, and it distinguishes from the sibling tools (which are unrelated business, GitHub, stack, and search tools). An agent can immediately understand the operation without ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 fetch an RSSHub route, but it does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives. Since the sibling tools are clearly different in purpose, the usage context is somewhat inferred but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search the public web through a live SearXNG instance pool.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover readOnly, openWorld, idempotent, and destructive false, and the description does not contradict them. However, it adds no additional behavioral details such as result formatting, potential errors, 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no redundant or extraneous words, making it easy to parse and understand.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the complete schema, and the read-only annotations, the description provides enough context for an agent to understand what the tool does and how to invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema fully documents both parameters with types and constraints, so the description does not need to restate them. Baseline score of 3 is appropriate since there is no parameter description but schema coverage is complete.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Search') and resource ('public web'), and the reference to a 'live SearXNG instance pool' distinguishes it from the sibling tools like rsshub_fetch and github_job_template.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or use cases. An agent would have to infer that this is for general web search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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