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datalens-dev-mcp

datalens-dev-mcp

by ADIKANT
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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dl_object_get

Read-onlyIdempotent

Fetch a DataLens object by ID, branch, and optional revision to inspect its state or preserve full details before applying mutations.

Instructions

Read a known target by ID, branch and optional revision. chart (alias widget) accepts confirmed Editor/Wizard/QL subtypes and returns observed_identity; explicit subtypes remain strict. Mutations require the exact observed type. Use summary/projection for inspection, full state for preservation.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "object_type": "<object_type>",
      "object_id": "<object_id>"
    },
    "name": "dl_object_get"
  }
}

Input Schema

NameRequiredDescriptionDefault
viewNofull
branchNosaved
fieldsNo
object_idYes
object_typeYes
revision_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.2.27
    • addedInput schema / properties / object_type / enum
      Added value: +[
+  "chart",
+  "widget",
+  "editor_chart",
+  "wizard_chart",
+  "ql_chart",
+  "dashboard",
+  "dash",
+  "dataset",
+  "connection",
+  "workbook",
+  "html_page",
+  "advanced_chart",
+  "advanced-chart_node",
+  "table_node",
+  "d3_node",
+  "markdown_node",
+  "control_node"
+]
    • removedInput schema / properties / object_type / minLength
      Removed value: -1
  2. Addedv1.2.0

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld), so the description correctly spends its budget elsewhere: alias resolution for chart/widget, the returned observed_identity, and strict subtype handling. That alias-resolution behavior is materially useful context an agent could not get from annotations or schema, though error modes and auth requirements remain undisclosed.

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?

Three tight sentences with the core read behavior front-loaded; no filler. The mutation sentence is terse and jargon-dense ('observed type') but is not padding — it is load-bearing context for choosing this tool.

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

Completeness3/5

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

No output schema exists and schema coverage is 0% across 6 parameters, so the description carries the full explanatory burden. It covers type aliasing and view selection but omits the `fields` projection parameter, revision_id semantics, and the many node-type variants, making it only adequate for a tool of this complexity.

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 description coverage is 0%, so the description must carry parameter meaning, and it partially does: it explains object_type alias/strict semantics, branch, revision, and the view trade-off. It never mentions the `fields` parameter at all and gives no format guidance for revision_id, leaving real gaps.

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

Purpose4/5

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

States a specific verb and resource ('Read a known target by ID, branch and optional revision') and pins down which identifiers scope the read. It differentiates itself from write siblings implicitly by noting 'Mutations require the exact observed type', but never names an alternative read tool (dl_object_revisions, dl_object_relations), so routing relies on inference.

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

Usage Guidelines3/5

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

'Use summary/projection for inspection, full state for preservation' is genuine when-to-use guidance for the view parameter, and the type-strictness sentence implies when this tool is required before a mutation. However there is no explicit statement of when NOT to use this tool, nor any pointer to sibling read tools.

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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