Syftly
Server Details
Ranks the best AI tool or API per task: transcription, TTS, web search, scraping and OCR.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Managed credentials
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 4/5 across 1 of 1 tools scored.
With only one tool, there is no risk of confusion. The tool's purpose is clear and distinct from any other tool, as there are no others.
The single tool name 'find_best_tool' follows a clear verb-noun pattern, which is consistent within the server's tool set.
Having only one tool feels thin for a server that claims to handle multiple domains (transcription, TTS, web search, etc.). While the tool is versatile, a broader scope would typically merit multiple tools.
The tool covers its stated categories well, with a parameter to disambiguate categories. Minor gaps like missing categories (e.g., image generation) are acceptable given the 'currently' qualifier.
Available Tools
1 toolfind_best_toolAInspect
Given a natural-language question about which AI tool or API is best for a task (currently transcription, text-to-speech, web search, scraping & browser and ocr & document extraction), return Syftly's ranked recommendation: a citeable summary, a provider table with prices and trade-offs, dated sources, and a confidence label. Optionally pass "category" to disambiguate; otherwise it is detected from the question.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The question in natural language, e.g. 'best transcription API for Dutch'. | |
| category | No | Optional category id to disambiguate the question; omit to let Syftly detect it. |
Output Schema
| Name | Required | Description |
|---|---|---|
| hap | Yes | Citeerbare kern, 40-80 words, reused verbatim across all views (ADR 0002). |
| slug | Yes | |
| query | Yes | The human question (page H1). |
| bronnen | Yes | |
| category | Yes | e.g. 'transcription'. |
| providers | Yes | |
| recommendation | Yes | |
| zekerheidslabel | Yes | Confidence/depth label (ADR 0001). |
| laatst_bijgewerkt | Yes | ISO date. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the output format (citeable summary, provider table, etc.) and the behavior of category detection/overriding. Since no annotations are provided, the description carries the full burden; it is adequate but does not mention potential limitations, data freshness, or cost implications.
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, well-structured sentence that front-loads the purpose and then lists the output components and optional parameter. Every part is necessary and adds value.
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 complexity (multi-component output, optional disambiguation), the description provides sufficient context for an AI agent to understand when and how to use it. The output schema is not shown, but the description outlines the return structure.
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 100%, so the baseline is 3. The description reinforces the schema by rephrasing the 'category' parameter's role but adds no new details beyond what the schema already provides.
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: given a natural-language question about which AI tool/API is best for specific tasks (transcription, TTS, web search, scraping, OCR), it returns a ranked recommendation with a citeable summary, provider table, prices, trade-offs, sources, and confidence label. The verb 'return' and the resource 'ranked recommendation' are specific, and the domain is explicitly listed.
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 explains when to use the tool (for tool/API recommendation questions) and how to optionally disambiguate via the 'category' parameter. However, it does not explicitly state when not to use it or exclude alternatives, which would be helpful for a general-purpose recommendation tool.
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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{
"$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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For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
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The server is experiencing an outage
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