smart-data-extractor
Server Details
smart-data-extractor MCP server on Cloudflare Workers · REST + MCP JSON-RPC · free tier
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- lazymac2x/smart-data-extractor-worker
- GitHub Stars
- 0
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Tool Definition Quality
Average 3.9/5 across 4 of 4 tools scored.
Each tool has a clear, distinct purpose: auto_schema_learn for schema inference, batch_extract for multi-source extraction, extract_from_api for API responses, and extract_from_url for URLs. No two tools overlap in their primary function.
Tool names use snake_case but with inconsistent patterns: 'auto_schema_learn' is adjective_noun_verb, while 'batch_extract' is noun_verb, and 'extract_from_api'/'extract_from_url' are verb_preposition_noun. This mismatch could confuse an agent.
Four tools is on the low side for a data extraction server, covering basic sources but lacking something like direct file extraction. The count is reasonable for a minimal server but feels slightly incomplete.
Covers schema learning and extraction from URLs, APIs, and batch sources, but missing extraction from local files, databases, or direct text input. No schema management or listing tools exist, leaving notable gaps.
Available Tools
4 toolsauto_schema_learnAInspect
Idempotent · 30s timeout · Automatically infer JSON Schema from sample data without extraction. Pass idempotency_key to deduplicate within 5 minutes.
| Name | Required | Description | Default |
|---|---|---|---|
| sample_data | Yes | Representative sample data as JSON string (array of objects or single object). Schema is inferred from structure; use first 1-10 rows for array samples. Max 200KB. | |
| idempotency_key | No | Optional cache key (UUID/string) for 5-minute deduplication. Repeat calls with same key return cached inferred schema instantly. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses idempotency (safe to retry), 30s timeout, and 5-minute deduplication window, adding behavioral context beyond the schema.
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 sentences with no wasted words, front-loading key attributes (idempotent, timeout, purpose). Highly efficient.
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 2-parameter tool with no output schema and no annotations, the description covers key behaviors and parameter roles adequately. Lacks return format details but acceptable for schema inference.
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%, so baseline is 3. The description adds deduplication context for idempotency_key but does not significantly extend beyond the schema for sample_data.
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 it infers JSON Schema from sample data without extraction, and it is distinct from sibling tools like batch_extract and extract_from_url which involve extraction.
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 mentions idempotency, timeout, and deduplication, implying use for schema inference from samples. It does not explicitly state when not to use, but sibling names provide sufficient differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
batch_extractAInspect
Idempotent · 30s timeout · Extract data from multiple sources (JSON/JSONL/text) with a single consistent schema. Pass idempotency_key to deduplicate within 5 minutes.
| Name | Required | Description | Default |
|---|---|---|---|
| schema | No | Optional target JSON Schema (draft-07) applied to all sources. If omitted, inferred from first source and reused across remaining sources. Enables consistent field extraction from diverse formats. | |
| sources | Yes | Array of 1-100 data sources to extract from. Each source includes type (format) and content (raw data). | |
| idempotency_key | No | Optional deduplication key (UUID/string) for 5-minute cache. Identical batch calls (same sources + schema + key) return cached results instantly. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses key behavioral traits: idempotent nature, 30-second timeout, 5-minute dedup cache via idempotency_key, and schema inference behavior. Without annotations, this adds valuable context, though error handling and output format are omitted.
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 sentences, no redundancy, front-loaded with key traits (idempotent, timeout) and core function. Every word 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 complexity (nested objects, no output schema), the description should mention the expected return format or error behavior. It covers idempotency and timeout but lacks guidance on output structure or failure modes.
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% with adequate descriptions for each parameter. The description reinforces the idempotency_key's dedup purpose but does not add significant new meaning 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 'Extract data from multiple sources (JSON/JSONL/text) with a single consistent schema', specifying the verb, resource, and scope. It implicitly distinguishes from siblings like 'extract_from_api' and 'extract_from_url' by focusing on local content extraction.
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 context (batch extraction with consistent schema) but does not explicitly state when to use this tool versus alternatives like 'auto_schema_learn' or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
extract_from_apiAInspect
Idempotent · 30s timeout · Extract structured data from API response JSON with schema adaptation. Pass idempotency_key to deduplicate within 5 minutes.
| Name | Required | Description | Default |
|---|---|---|---|
| schema | No | Optional target JSON Schema (draft-07) for field extraction. If omitted, inferred from content structure. Enforces consistent field extraction across multiple API responses. | |
| content | Yes | API response body as raw JSON string (max 200KB). Can be single object, array of objects, or array of primitives. Automatically parsed and validated. | |
| idempotency_key | No | Optional deduplication key (UUID or unique string) for 5-minute cache. Identical calls return cached result instantly. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral disclosure. It mentions idempotency (safe to retry), a 30-second timeout, and a 5-minute deduplication window via idempotency_key. This goes beyond basic purpose. However, it lacks details on error handling, response format, or limits beyond the 200KB content constraint.
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 concise sentences: the first front-loads key behaviors (idempotent, timeout, core action), the second provides a specific parameter usage hint. No wasted words; the structure efficiently conveys the tool's essence.
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 covers purpose and key behaviors but omits the return value format (no output schema exists), error scenarios, and how schema adaptation works in detail. Given the tool's complexity (nested objects, multiple structures), this omission leaves some contextual gaps.
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?
All three parameters are already described in the input schema (100% coverage). The description adds value by specifying the deduplication window for idempotency_key and reinforcing schema inference for the 'schema' parameter. However, it largely repeats the schema, so the additional semantic contribution is moderate.
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: 'Extract structured data from API response JSON with schema adaptation'. The verb 'extract' and resource 'API response JSON' are specific. It distinguishes from siblings by focusing on raw API response input, as opposed to auto_schema_learn (learning schemas) or extract_from_url (fetching from URL).
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 usage for extracting structured data from API response JSON, but does not provide explicit when-to-use or when-not-to-use guidance compared to sibling tools like batch_extract or extract_from_url. No exclusions or alternative recommendations are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
extract_from_urlAInspect
Idempotent · 30s timeout · Extract structured data from URL content with auto schema learning. Pass idempotency_key to deduplicate identical calls within 5 minutes.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | HTTP(S) URL to fetch (will auto-download and parse), or raw content string (up to 200KB). Max 200KB after fetch. | |
| schema | No | Optional pre-defined JSON Schema (draft-07). If omitted, schema is auto-inferred from content. Provide to enforce strict field extraction and type coercion. | |
| idempotency_key | No | Optional UUID or unique identifier for 5-minute deduplication cache. Same key + tool = cached result in <5ms, zero re-fetching. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description discloses important behavioral traits: idempotency, a 30-second timeout, auto schema learning, and deduplication with an idempotency key. This is valuable for an agent to understand the tool's behavior.
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 extremely concise, with two front-loaded sentences that pack key information (idempotent, timeout, extraction function, deduplication). Every word earns its place, no 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?
Without an output schema, the description could clarify the return format (e.g., JSON object). It mentions 'structured data' but is vague. For a tool with moderate complexity, it provides essential behavior but lacks a complete picture of inputs and outputs.
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 already provides detailed descriptions for all three parameters (100% coverage). The description adds minimal extra value, only mentioning idempotency key deduplication, which echoes the schema's description.
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 extracts structured data from URL content with auto schema learning. It uses a specific verb 'Extract' and resource 'URL content', but does not differentiate from sibling tools like 'batch_extract' or 'extract_from_api'.
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 its siblings (auto_schema_learn, batch_extract, extract_from_api). The description lacks context about prerequisites or scenarios where this tool is preferred.
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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