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Obsidian MCP Extended

Obsidian MCP Extended

by aleksakarac
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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table_query_dql_tool

Execute DQL TABLE queries to create tabular views of Obsidian notes with custom fields for structured data analysis, reports, and dashboards.

Instructions

Execute a DQL TABLE query (requires Obsidian + Dataview plugin).

Creates tabular views of note metadata with custom fields.

When to use:

  • Creating structured data views

  • Displaying multiple fields in table format

  • Building reports and dashboards

  • Analyzing note collections

Returns: Table results with specified fields and rows

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": {
      "fields": "<fields>"
    },
    "name": "table_query_dql_tool"
  }
}

Input Schema

NameRequiredDescriptionDefault
fieldsYesList of fields to display
from_clauseNoFROM clause (e.g., '#project', '"folder"')
where_clauseNoOptional WHERE filter
sort_byNoOptional SORT clause
limitNoOptional result limit
ctxNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.1.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It mentions the dependency on Obsidian and Dataview and states returns table results, but does not disclose whether the tool is read-only (likely yes) or any side effects, permissions, or performance considerations.

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?

The description is well-organized with a clear first sentence, bullet points for usage, and a return section. It is concise and front-loaded, though the bullet points could be more precise.

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?

Given the number of parameters and lack of output schema, the description covers the core purpose and typical use cases. However, it omits practical details like valid field names, query limitations, or how it differs from execute_dataview_query_tool.

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 83%, so most parameters have descriptions. The description adds minimal extra meaning beyond the schema, only providing examples of fields. It does not explain how parameters interact or format details.

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?

Description clearly states it executes a DQL TABLE query to create tabular views of note metadata. It lists use cases like creating reports and dashboards, but does not explicitly distinguish from sibling tools like execute_dataview_query_tool that might handle other DQL query types.

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?

The 'When to use' section provides four scenarios, giving some context. However, it lacks explicit guidance on when not to use this tool or how it compares to alternatives like list_notes_by_folder_dql_tool or search_by_dataview_field_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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