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rawtreedb

RawTree MCP Server

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by rawtreedb

Insert From URL

insert-from-url

Ingest JSON or JSONL data from a public URL into a RawTree table. Streams progress as NDJSON.

Instructions

Purpose: Ask RawTree to ingest JSON/JSONL data from a public URL into a table. RawTree streams progress as NDJSON.

NOT for: Private files on your machine, authenticated URLs, or built-in transforms. Host transformed data first or use insert-json with transform.

Returns: The RawTree NDJSON progress stream as text.

When to use:

  • User has a public JSON or JSONL file URL

  • You need RawTree to fetch and ingest the file directly

  • The data is too large or inconvenient to paste into the MCP call

Workflow: Confirm the URL is public → call insert-from-url → use list-logs and run-query to verify.

Key trigger phrases: "ingest this URL", "load JSONL from", "import from public file"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableYesTarget table name.
urlYesPublic URL containing data RawTree can fetch.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses streaming progress as NDJSON and return format. No annotations, so description carries full burden. Missing details on whether ingestion is append/overwrite and error handling, but overall good transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with clear headings, front-loaded purpose, and no superfluous content. Every section adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Includes return value description, workflow, and usage hints. Missing details on table existence requirements and error scenarios, but sufficient given tool simplicity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with adequate descriptions. The description adds no additional parameter semantics beyond confirming URL must be public; baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool ingests JSON/JSONL from a public URL into a table. Distinguishes from siblings like insert-json and explicitly lists exclusions (private files, authenticated URLs).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when-to-use, when-not-to-use, and alternatives. Includes a workflow and key trigger phrases, covering context comprehensively.

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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