Taproot: AT Protocol MCP

get_backlinks

Read-only

Index of who/what references a target,the inbound likes, reposts, quotes, replies, and follows,as COUNTS per category, via the Constellation backlink index. Target is a record's at:// URI or an account DID. This returns aggregate counts only; each category also includes a source string. To list the actual records and their author DIDs for one category (e.g. WHO liked a post), call list_backlink_records with that source.

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": {
      "target": "<target>"
    },
    "name": "get_backlinks"
  }
}

Input Schema

Name	Required	Description	Default
`target`	Yes	A record at:// URI or a DID.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 13, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already cover readOnly and openWorld, so the description focuses on added context: results are aggregate counts only, each category carries a `source` string, and the data comes from the Constellation backlink index. It stops short of describing shape/pagination, but the output schema covers return values, so this is solid added value.

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-loads the resource and its output shape, then routes to the alternative. Efficient overall, though the comma-spliced category list makes the first sentence denser than necessary.

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

Completeness5/5

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

For a single-param aggregate-read tool with an output schema, the description covers what is returned (counts per category), the target formats, and the sibling handoff. Nothing an agent needs to select and invoke it correctly is missing.

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% and the schema already documents `target` as 'A record at:// URI or a DID.' The description restates the same accepted formats (at:// URI or DID) without adding syntax, constraints, or examples beyond the schema. 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 resource (backlink index) with the exact categories it aggregates (likes, reposts, quotes, replies, follows) and clarifies it returns COUNTS, which is the key differentiator. It also names the sibling list_backlink_records so an agent can immediately tell the two apart.

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?

Explicitly gives the when-to-use-this vs. when-to-use-alternative rule: use this for aggregate counts, and 'to list the actual records and their author DIDs for one category... call list_backlink_records with that source.' The switching condition and handoff parameter are spelled out.

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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