An MCP endpoint for connecting with Fikra API
Scored across 2 tools
The two tools have clearly distinct purposes: fikra_chat generates responses, while fikra_list_models lists available models. There is no overlap or ambiguity between them.
Both tool names follow the exact same fikra_ prefix and snake_case verb_noun pattern (fikra_chat, fikra_list_models). This is fully consistent and predictable.
With only 2 tools, the surface feels thin for a chat model service. While the two operations cover a minimal workflow, additional capabilities (e.g., model details, streaming) could reasonably be expected.
The core lifecycle of listing models and sending a chat request is covered. Minor gaps exist, such as no way to retrieve conversation history or manage API keys, but these are not critical for basic usage.
Generate a response with a Fikra model. Paid per call (x402 USDC or API key).
| Name | Required | Description | Default |
|---|---|---|---|
| model | No | ||
| messages | Yes | ||
| max_tokens | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, and it does disclose the notable behavioral trait of cost and auth ('Paid per call (x402 USDC or API key)'). It still omits output format, latency/streaming behavior, failure modes on insufficient payment, and whether generation is deterministic.
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?
Two short sentences with the core action front-loaded and the payment condition appended; no filler. Slightly terse given how much is left unspecified, but nothing is wasted.
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?
There is no output schema, no annotations, and 0% schema coverage, so the description is the only source of truth. It fails to explain the return shape, the messages array format, or what a caller should do after listing models, leaving an agent under-equipped for this paid generative call.
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% with 3 parameters (model, messages, max_tokens), so the description must compensate and largely does not. 'with a Fikra model' only obliquely hints at the model parameter, and the shape of messages and the meaning of max_tokens are left entirely undocumented.
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?
States a specific verb+resource: 'Generate a response with a Fikra model.' It is clearly distinguishable in kind from the sibling fikra_list_models, though the description never names that sibling to reinforce the split.
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 when-to-use or when-not-to-use guidance and no mention of the sibling fikra_list_models as the prerequisite for discovering a model name. Usage is only weakly implied by 'chat' semantics.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List available Fikra chat models with prices. Free.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the burden; it does disclose the return content ('with prices') and cost ('Free'), which is meaningful for a zero-parameter tool. It does not say whether the list is exhaustive or ordered, so transparency is adequate but thin.
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?
Two short, front-loaded sentences with no filler; the purpose leads and the cost note follows. The fragment 'Free.' is terse but earns its place by answering a likely agent question.
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 zero-parameter, no-output-schema discovery tool the definition is largely sufficient: it names the resource and the shape of the result (models plus prices). Minor omissions are ordering/exhaustiveness, which are unlikely to block correct invocation.
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 zero parameters, so there is nothing for the description to disambiguate. The baseline of 4 applies; 'with prices' adds a note about return content rather than parameter meaning.
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?
States a specific verb ('List') and resource ('Fikra chat models') and adds an attributed detail ('with prices'). The sibling fikra_chat is distinct in kind (a chat action vs a discovery list), but the description never explicitly contrasts the two, so it stays below the 5 bar.
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?
'Free.' signals there is no cost barrier, which is usable context, but there is no explicit when-to-use statement or reference to fikra_chat as the follow-on action. Usage is implied by the list-models purpose rather than stated.
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.
fikra_chatfikra_list_models
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