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ragflow-kb-mcp

ragflow-kb-mcp

by feci
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

ragflow_agent_chat

Send a message to a RAGFlow agent and receive its complete answer. Continue an existing session or start a new one, optionally attaching uploaded files and Begin-component input values.

Instructions

Send a message to an agent and wait for its complete answer.

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": {
      "agent_id": "<agent_id>"
    },
    "name": "ragflow_agent_chat"
  }
}

Input Schema

NameRequiredDescriptionDefault
filesNoFile objects returned by ragflow_upload_agent_file
inputsNoValues for the Begin component's input fields, keyed by field name: a plain value or {"value": ...}
agent_idYesAgent ID
questionNoThe user's message; may be empty when the agent only takes inputs
session_idNoContinue this session; without it RAGFlow starts a new session and returns its id
openai_compatibleNoUse RAGFlow's OpenAI-compatible mode, which also reports token usage; the agent run is the same

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

B3.3/5.0
Behavior3/5

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

Annotations declare openWorldHint=true and destructiveHint=false, so the safety profile is partly covered. The description usefully adds that the call blocks until the full answer is returned, but says nothing about latency, streaming absence, or session-creation side effects beyond what the schema states.

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

Conciseness5/5

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

One sentence, zero padding, with the blocking behavior front-loaded as the key differentiator.

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?

An output schema exists and the schema documents parameters well, but the description omits the session lifecycle (agent_id/session_id relationship) and how files/inputs flow into a call, which matter for an agent-driven chat 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 description coverage is 100%, including the important note that omitting session_id starts a new session and returns its id. The description adds no parameter detail beyond the schema, so baseline 3 applies.

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 ('send a message to an agent') plus a meaningful behavioral trait ('wait for its complete answer'). It does not, however, distinguish itself from close siblings like ragflow_chat, ragflow_openai_chat_completion, or ragflow_create_agent_session.

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

Usage Guidelines2/5

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

There is no guidance on when to use this instead of ragflow_chat, ragflow_openai_chat_completion, or the session tools, and no mention of prerequisites such as requiring files uploaded via ragflow_upload_agent_file (that link lives only in the schema).

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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