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RawTree MCP Server

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Insert JSON

insert-json

Send events, logs, or records by inserting JSON objects into RawTree tables, which are auto-created on first insert.

Instructions

Purpose: Insert one JSON object or an array of JSON objects into a RawTree table. RawTree auto-creates the table on first insert.

NOT for: Loading data from a public URL (use insert-from-url).

Returns: Insert confirmation, usually { "inserted": }.

When to use:

  • User wants to send events, logs, traces, metrics, or arbitrary records to RawTree

  • You need to create a table by inserting the first row

  • You need to validate that RawTree accepts a payload shape

Workflow: Choose a table name → send a small representative payload → run describe-table or run-query to verify.

Key trigger phrases: "insert this", "send event", "write to RawTree", "create table with data", "ingest JSON"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesA JSON object or a non-empty array of JSON objects to insert.
tableYesTarget table name. RawTree accepts identifiers like events, traces, api_logs.
clusterNoRawTree cluster to use for this operation.
databaseNoOptional RawTree database override. RawTree uses the default database when omitted.
organizationNoRawTree organization containing the target cluster.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changedv0.3.2
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • addedInput schema / properties / cluster
      Added value: +{
+  "description": "RawTree cluster to use for this operation.",
+  "minLength": 1,
+  "type": "string"
+}
    • removedInput schema / properties / columns
      Removed value: -{
-  "description": "For transform=firehose only: TSV column names matching each Firehose record line.",
-  "items": {
-    "minLength": 1,
-    "type": "string"
-  },
-  "type": "array"
-}
    • addedInput schema / properties / database
      Added value: +{
+  "description": "Optional RawTree database override. RawTree uses the default database when omitted.",
+  "minLength": 1,
+  "type": "string"
+}
    • addedInput schema / properties / organization
      Added value: +{
+  "description": "RawTree organization containing the target cluster.",
+  "minLength": 1,
+  "type": "string"
+}
    • removedInput schema / properties / transform
      Removed value: -{
-  "description": "Optional RawTree built-in transform for JSON body inserts: otlp-traces, otlp-logs, otlp-metrics, cloudwatch-logs, cloudtrail, or firehose.",
-  "enum": [
-    "otlp-traces",
-    "otlp-logs",
-    "otlp-metrics",
-    "cloudwatch-logs",
-    "cloudtrail",
-    "firehose"
-  ],
-  "type": "string"
-}
  2. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses auto table creation on first insert, the return shape ({inserted: n}), and a verification workflow. It omits auth/permission requirements, failure modes, and behavior on schema conflicts, leaving some gaps for a write tool.

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

Conciseness4/5

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

Front-loaded with Purpose, NOT for, Returns, When to use, and Workflow. Structured and scannable, though the trigger-phrase list is somewhat redundant with the When-to-use bullets.

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?

Covers purpose, exclusions, return shape, workflow, and verification steps without an output schema. Adequate for a write tool, though auth context and error behavior are absent.

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%, so the schema already documents all five parameters. The description adds little parameter-level meaning beyond the payload workflow narrative. Baseline 3 is appropriate when the schema does the heavy lifting.

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?

States a specific verb (Insert) and resource (JSON objects into a RawTree table), and explicitly distinguishes from the sibling insert-from-url. The auto-create-table behavior is a concrete distinguishing trait.

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 an explicit 'When to use' list with three concrete triggers, a 'NOT for' exclusion naming the sibling alternative insert-from-url, and key trigger phrases. Routing is unambiguous.

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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