Persistent project context — Rust-native MCP server. IANA-registered .faf format.
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Average 3.2/5 across 3 of 3 tools scored.
Each tool has a clearly distinct purpose: reading/normalizing, scoring completeness, and validating with errors/warnings. Even though faf_score and faf_validate both return a score, the validation adds diagnostic information, reducing overlap.
All three tools follow a consistent faf_verb pattern using snake_case, with verbs 'read', 'score', and 'validate'. No mixing of conventions or unclear names.
Three tools is a well-scoped set for a specialized server handling .faf files. It covers essential operations without being bloated or insufficient for the niche domain.
The server covers reading, scoring, and validating .faf files, which are key analysis operations. However, it lacks tools for creating, writing, or modifying .faf files, which may be a gap depending on use case.
faf_readCInspectParse a .faf and return its normalized structure (Rust→WASM, at the edge).
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | Raw .faf file content (YAML) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It mentions 'normalized structure' but does not discuss side effects, performance, error behavior, or safety. The parse operation is likely read-only but unstated.
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 very short (one sentence) with no wasted words. However, it includes the parenthetical '(Rust→WASM, at the edge)' which is not essential for understanding the tool's function.
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?
Since no output schema exists, the description should elaborate on the return value beyond 'normalized structure'. It lacks details on error handling, encoding, or the structure format, making it incomplete for a parsing tool.
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 coverage is 100% and the single parameter 'content' is described. The tool description adds no extra meaning beyond the schema's 'Raw .faf file content (YAML)'.
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 it parses a .faf file and returns a normalized structure, clearly indicating the verb and resource. It distinguishes from siblings (faf_score, faf_validate) by implying different functions, but the technology detail (Rust→WASM) is not essential for tool selection.
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 on when to use this tool versus alternatives like faf_score or faf_validate. The description does not mention prerequisites, when-not-to-use, or context for invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
faf_scoreBInspectScore a .faf — 0-100 completeness (Rust→WASM, at the edge).
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | Raw .faf file content (YAML) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description fails to disclose side effects, mutability, or constraints like idempotency or rate limits. 'Score' suggests a safe computation, but no confirmation.
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?
Single, front-loaded sentence with no waste. Efficiently communicates core purpose and context.
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?
Missing behavioral details, usage scenarios, and return format; with no output schema nor annotations, description is insufficient for a standalone tool.
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 coverage 100%; parameter 'content' already described as 'Raw .faf file content (YAML)' in schema. Description adds no additional meaning beyond the schema.
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 verb 'Score' and resource '.faf' with specific output range '0-100 completeness' and context 'Rust→WASM, at the edge', distinguishing from sibling tools read/validate.
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 explicit when-to-use or alternatives provided; usage is implied but not contrasted with sibling tools or edge cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
faf_validateBInspectValidate a .faf and return completeness score + errors/warnings (Rust→WASM, at the edge).
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | Raw .faf file content (YAML) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that validation runs via Rust→WASM at the edge, and that it returns diagnostic information (errors/warnings). However, without annotations, it does not state whether the operation is read-only, idempotent, or has side effects, which is moderately informative for a validation tool.
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?
A single concise sentence that immediately states the tool's purpose and key output. Every part contributes value with no wasted words.
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 validation tool with one parameter and no output schema, the description is mostly complete: it states the action, input, and return type. Minor omissions like error handling or size limits exist but are not critical given the tool's straightforward nature.
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 input schema covers 100% of parameters and already describes 'content' as 'Raw .faf file content (YAML)'. The description adds no further meaning, so it meets the baseline but does not exceed it.
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 verb 'Validate' and the resource '.faf file', and specifies the output: completeness score plus errors/warnings. This distinguishes it from sibling tools 'faf_read' and 'faf_score' by the action performed, though it does not explicitly contrast them.
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 over alternatives. The description only implies validation, but does not state preconditions, exclusions, or mention alternative tools for scoring or reading.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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