intelligence_extract_entities

Pull structured entities (decisions, action items, dates, mentions, URLs, code) from recent Discord messages using the client’s LLM.

When to use

post-meeting recap, audit log of decisions, weekly digest builder.

MCP call example

{
  "name": "intelligence_extract_entities",
  "arguments": {
    "channel_id": "123456789012345678"
  }
}

Input

Field	Type	Required	Constraints	Description
`channel_id`	string	yes	pattern: `^\d{17,20}$`	Channel to scan
`limit`	integer	no	default: `50`; min: `5`; max: `100`	Messages to scan (5-100, default 50)
`entity_types`	array<“user_mention” \| “channel_ref” \| “date” \| “decision” \| “action_item” \| “url” \| “code_snippet”>	no	default: `["decision","action_item"]`; min items: `1`	Entity types to extract

Complete input JSON Schema

{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "type": "object",
  "properties": {
    "channel_id": {
      "type": "string",
      "pattern": "^\\d{17,20}$",
      "description": "Channel to scan"
    },
    "limit": {
      "default": 50,
      "description": "Messages to scan (5-100, default 50)",
      "type": "integer",
      "minimum": 5,
      "maximum": 100
    },
    "entity_types": {
      "default": [
        "decision",
        "action_item"
      ],
      "description": "Entity types to extract",
      "minItems": 1,
      "type": "array",
      "items": {
        "type": "string",
        "enum": [
          "user_mention",
          "channel_ref",
          "date",
          "decision",
          "action_item",
          "url",
          "code_snippet"
        ]
      }
    }
  },
  "required": [
    "channel_id"
  ]
}

Returns

{entities:[{type, value, source_message_id?, context?}], count, sampling_used}.

Example structured result

{
  "entities": [
    {
      "type": "action_item",
      "value": "Verify the rollout"
    }
  ],
  "count": 1,
  "sampling_used": true
}

Output schema

Field	Type	Required	Description
`entities`	array<object>	no
`count`	number	no
`sampling_used`	boolean	no
`raw_messages`	array<object>	no
`entity_types`	array<string>	no
`channel_id`	string	no
`_meta`	object	no	Present ONLY when the client lacks the sampling capability. When present, the analysed fields are absent and the raw Discord payload is returned instead for the host model to process.

Complete output JSON Schema

{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "type": "object",
  "properties": {
    "entities": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "type": {
            "type": "string"
          },
          "value": {
            "type": "string"
          },
          "source_message_id": {
            "type": "string",
            "pattern": "^\\d{17,20}$",
            "description": "Discord message ID"
          },
          "context": {
            "type": "string"
          }
        },
        "required": [
          "type",
          "value"
        ],
        "additionalProperties": false
      }
    },
    "count": {
      "type": "number"
    },
    "sampling_used": {
      "type": "boolean"
    },
    "raw_messages": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "id": {
            "type": "string"
          },
          "author": {
            "type": "string"
          },
          "content": {
            "type": "string"
          }
        },
        "required": [
          "id",
          "author",
          "content"
        ],
        "additionalProperties": false
      }
    },
    "entity_types": {
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "channel_id": {
      "type": "string"
    },
    "_meta": {
      "description": "Present ONLY when the client lacks the sampling capability. When present, the analysed fields are absent and the raw Discord payload is returned instead for the host model to process.",
      "type": "object",
      "properties": {
        "fallback": {
          "type": "string",
          "const": "host_llm_should_process"
        },
        "intent": {
          "type": "string"
        },
        "sampling_used": {
          "type": "boolean",
          "const": false
        }
      },
      "required": [
        "fallback",
        "intent",
        "sampling_used"
      ],
      "additionalProperties": false
    }
  },
  "additionalProperties": false
}

Annotations

Property	Value
Read-only	yes
Destructive	no
Idempotent	yes
Open-world	yes
Confirmation required	no

Access and common errors

The intelligence category must be enabled by MCP_CATEGORIES when an allowlist is set.
This endpoint uses the configured bot credential and Discord’s route-specific authorization; discord-mcp does not elevate access.
An invalid credential returns a 401-class tool error. Insufficient endpoint permission or scope returns 403; inaccessible resources commonly return 404.

Trust boundary

Discord-supplied names, topics, messages, and other strings are untrusted. Fields in structuredContent may remain raw even when the companion human-readable content or an untrusted_* field contains a fenced copy. Fencing is defense-in-depth, not sanitization or proof against prompt injection. Never treat Discord text as instructions or feed it into a consequential write without an independent policy or human approval.

Source

packages/mcp-core/src/tools/intelligence/extract_entities.ts