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revert white-space changes in docs (#12557)

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### What problem does this PR solve?

Trailing white-spaces in commit 6814ace1aa
got automatically trimmed by code editor may causes documentation
typesetting broken.

Mostly for double spaces for soft line breaks.  

### Type of change

- [x] Documentation Update
This commit is contained in:
Jimmy Ben Klieve
2026-01-13 09:41:02 +08:00
committed by GitHub
parent fd0a1fde6b
commit 867ec94258
71 changed files with 660 additions and 731 deletions
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61
docs/develop/mcp/launch_mcp_server.md
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@ -5,20 +5,19 @@ sidebar_custom_props: {
categoryIcon: LucideTvMinimalPlay
}
---
# Launch RAGFlow MCP server
Launch an MCP server from source or via Docker.
---
A RAGFlow Model Context Protocol (MCP) server is designed as an independent component to complement the RAGFlow server. Note that an MCP server must operate alongside a properly functioning RAGFlow server.
A RAGFlow Model Context Protocol (MCP) server is designed as an independent component to complement the RAGFlow server. Note that an MCP server must operate alongside a properly functioning RAGFlow server.
An MCP server can start up in either self-host mode (default) or host mode:
An MCP server can start up in either self-host mode (default) or host mode:
- **Self-host mode**:
- **Self-host mode**:
When launching an MCP server in self-host mode, you must provide an API key to authenticate the MCP server with the RAGFlow server. In this mode, the MCP server can access *only* the datasets of a specified tenant on the RAGFlow server.
- **Host mode**:
- **Host mode**:
In host mode, each MCP client can access their own datasets on the RAGFlow server. However, each client request must include a valid API key to authenticate the client with the RAGFlow server.
Once a connection is established, an MCP server communicates with its client in MCP HTTP+SSE (Server-Sent Events) mode, unidirectionally pushing responses from the RAGFlow server to its client in real time.
@ -32,9 +31,9 @@ Once a connection is established, an MCP server communicates with its client in
If you wish to try out our MCP server without upgrading RAGFlow, community contributor [yiminghub2024](https://github.com/yiminghub2024) 👏 shares their recommended steps [here](#launch-an-mcp-server-without-upgrading-ragflow).
:::
## Launch an MCP server
## Launch an MCP server
You can start an MCP server either from source code or via Docker.
You can start an MCP server either from source code or via Docker.
### Launch from source code
@ -51,7 +50,7 @@ uv run mcp/server/server.py --host=127.0.0.1 --port=9382 --base-url=http://127.0
# uv run mcp/server/server.py --host=127.0.0.1 --port=9382 --base-url=http://127.0.0.1:9380 --mode=host
```
Where:
Where:
- `host`: The MCP server's host address.
- `port`: The MCP server's listening port.
@ -97,7 +96,7 @@ The MCP server is designed as an optional component that complements the RAGFlow
# - --no-json-response # Disables JSON responses for the streamable-HTTP transport
```
Where:
Where:
- `mcp-host`: The MCP server's host address.
- `mcp-port`: The MCP server's listening port.
@ -122,13 +121,13 @@ Run `docker compose -f docker-compose.yml up` to launch the RAGFlow server toget
docker-ragflow-cpu-1 | Starting MCP Server on 0.0.0.0:9382 with base URL http://127.0.0.1:9380...
docker-ragflow-cpu-1 | Starting 1 task executor(s) on host 'dd0b5e07e76f'...
docker-ragflow-cpu-1 | 2025-04-18 15:41:18,816 INFO 27 ragflow_server log path: /ragflow/logs/ragflow_server.log, log levels: {'peewee': 'WARNING', 'pdfminer': 'WARNING', 'root': 'INFO'}
docker-ragflow-cpu-1 |
docker-ragflow-cpu-1 |
docker-ragflow-cpu-1 | __ __ ____ ____ ____ _____ ______ _______ ____
docker-ragflow-cpu-1 | | \/ |/ ___| _ \ / ___|| ____| _ \ \ / / ____| _ \
docker-ragflow-cpu-1 | | |\/| | | | |_) | \___ \| _| | |_) \ \ / /| _| | |_) |
docker-ragflow-cpu-1 | | | | | |___| __/ ___) | |___| _ < \ V / | |___| _ <
docker-ragflow-cpu-1 | |_| |_|\____|_| |____/|_____|_| \_\ \_/ |_____|_| \_\
docker-ragflow-cpu-1 |
docker-ragflow-cpu-1 |
docker-ragflow-cpu-1 | MCP launch mode: self-host
docker-ragflow-cpu-1 | MCP host: 0.0.0.0
docker-ragflow-cpu-1 | MCP port: 9382
@ -141,13 +140,13 @@ Run `docker compose -f docker-compose.yml up` to launch the RAGFlow server toget
docker-ragflow-cpu-1 | 2025-04-18 15:41:23,263 INFO 27 init database on cluster mode successfully
docker-ragflow-cpu-1 | 2025-04-18 15:41:25,318 INFO 27 load_model /ragflow/rag/res/deepdoc/det.onnx uses CPU
docker-ragflow-cpu-1 | 2025-04-18 15:41:25,367 INFO 27 load_model /ragflow/rag/res/deepdoc/rec.onnx uses CPU
docker-ragflow-cpu-1 | ____ ___ ______ ______ __
docker-ragflow-cpu-1 | ____ ___ ______ ______ __
docker-ragflow-cpu-1 | / __ \ / | / ____// ____// /____ _ __
docker-ragflow-cpu-1 | / /_/ // /| | / / __ / /_ / // __ \| | /| / /
docker-ragflow-cpu-1 | / _, _// ___ |/ /_/ // __/ / // /_/ /| |/ |/ /
docker-ragflow-cpu-1 | /_/ |_|/_/ |_|\____//_/ /_/ \____/ |__/|__/
docker-ragflow-cpu-1 |
docker-ragflow-cpu-1 |
docker-ragflow-cpu-1 | / _, _// ___ |/ /_/ // __/ / // /_/ /| |/ |/ /
docker-ragflow-cpu-1 | /_/ |_|/_/ |_|\____//_/ /_/ \____/ |__/|__/
docker-ragflow-cpu-1 |
docker-ragflow-cpu-1 |
docker-ragflow-cpu-1 | 2025-04-18 15:41:29,088 INFO 27 RAGFlow version: v0.18.0-285-gb2c299fa full
docker-ragflow-cpu-1 | 2025-04-18 15:41:29,088 INFO 27 project base: /ragflow
docker-ragflow-cpu-1 | 2025-04-18 15:41:29,088 INFO 27 Current configs, from /ragflow/conf/service_conf.yaml:
@ -156,12 +155,12 @@ Run `docker compose -f docker-compose.yml up` to launch the RAGFlow server toget
docker-ragflow-cpu-1 | * Running on all addresses (0.0.0.0)
docker-ragflow-cpu-1 | * Running on http://127.0.0.1:9380
docker-ragflow-cpu-1 | * Running on http://172.19.0.6:9380
docker-ragflow-cpu-1 | ______ __ ______ __
docker-ragflow-cpu-1 | ______ __ ______ __
docker-ragflow-cpu-1 | /_ __/___ ______/ /__ / ____/ _____ _______ __/ /_____ _____
docker-ragflow-cpu-1 | / / / __ `/ ___/ //_/ / __/ | |/_/ _ \/ ___/ / / / __/ __ \/ ___/
docker-ragflow-cpu-1 | / / / /_/ (__ ) ,< / /____> </ __/ /__/ /_/ / /_/ /_/ / /
docker-ragflow-cpu-1 | /_/ \__,_/____/_/|_| /_____/_/|_|\___/\___/\__,_/\__/\____/_/
docker-ragflow-cpu-1 |
docker-ragflow-cpu-1 | / / / /_/ (__ ) ,< / /____> </ __/ /__/ /_/ / /_/ /_/ / /
docker-ragflow-cpu-1 | /_/ \__,_/____/_/|_| /_____/_/|_|\___/\___/\__,_/\__/\____/_/
docker-ragflow-cpu-1 |
docker-ragflow-cpu-1 | 2025-04-18 15:41:34,501 INFO 32 TaskExecutor: RAGFlow version: v0.18.0-285-gb2c299fa full
docker-ragflow-cpu-1 | 2025-04-18 15:41:34,501 INFO 32 Use Elasticsearch http://es01:9200 as the doc engine.
...
@ -173,11 +172,11 @@ Run `docker compose -f docker-compose.yml up` to launch the RAGFlow server toget
This section is contributed by our community contributor [yiminghub2024](https://github.com/yiminghub2024). 👏
:::
1. Prepare all MCP-specific files and directories.
i. Copy the [mcp/](https://github.com/infiniflow/ragflow/tree/main/mcp) directory to your local working directory.
ii. Copy [docker/docker-compose.yml](https://github.com/infiniflow/ragflow/blob/main/docker/docker-compose.yml) locally.
iii. Copy [docker/entrypoint.sh](https://github.com/infiniflow/ragflow/blob/main/docker/entrypoint.sh) locally.
iv. Install the required dependencies using `uv`:
1. Prepare all MCP-specific files and directories.
i. Copy the [mcp/](https://github.com/infiniflow/ragflow/tree/main/mcp) directory to your local working directory.
ii. Copy [docker/docker-compose.yml](https://github.com/infiniflow/ragflow/blob/main/docker/docker-compose.yml) locally.
iii. Copy [docker/entrypoint.sh](https://github.com/infiniflow/ragflow/blob/main/docker/entrypoint.sh) locally.
iv. Install the required dependencies using `uv`:
- Run `uv add mcp` or
- Copy [pyproject.toml](https://github.com/infiniflow/ragflow/blob/main/pyproject.toml) locally and run `uv sync --python 3.12`.
2. Edit **docker-compose.yml** to enable MCP (disabled by default).
@ -197,7 +196,7 @@ docker logs docker-ragflow-cpu-1
## Security considerations
As MCP technology is still at early stage and no official best practices for authentication or authorization have been established, RAGFlow currently uses [API key](./acquire_ragflow_api_key.md) to validate identity for the operations described earlier. However, in public environments, this makeshift solution could expose your MCP server to potential network attacks. Therefore, when running a local SSE server, it is recommended to bind only to localhost (`127.0.0.1`) rather than to all interfaces (`0.0.0.0`).
As MCP technology is still at early stage and no official best practices for authentication or authorization have been established, RAGFlow currently uses [API key](./acquire_ragflow_api_key.md) to validate identity for the operations described earlier. However, in public environments, this makeshift solution could expose your MCP server to potential network attacks. Therefore, when running a local SSE server, it is recommended to bind only to localhost (`127.0.0.1`) rather than to all interfaces (`0.0.0.0`).
For further guidance, see the [official MCP documentation](https://modelcontextprotocol.io/docs/concepts/transports#security-considerations).
@ -205,11 +204,11 @@ For further guidance, see the [official MCP documentation](https://modelcontextp
### When to use an API key for authentication?
The use of an API key depends on the operating mode of your MCP server.
The use of an API key depends on the operating mode of your MCP server.
- **Self-host mode** (default):
When starting the MCP server in self-host mode, you should provide an API key when launching it to authenticate it with the RAGFlow server:
- If launching from source, include the API key in the command.
- **Self-host mode** (default):
When starting the MCP server in self-host mode, you should provide an API key when launching it to authenticate it with the RAGFlow server:
- If launching from source, include the API key in the command.
- If launching from Docker, update the API key in **docker/docker-compose.yml**.
- **Host mode**:
- **Host mode**:
If your RAGFlow MCP server is working in host mode, include the API key in the `headers` of your client requests to authenticate your client with the RAGFlow server. An example is available [here](https://github.com/infiniflow/ragflow/blob/main/mcp/client/client.py).

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@ -6,7 +6,6 @@ sidebar_custom_props: {
}
---
# RAGFlow MCP client examples
Python and curl MCP client examples.
@ -39,11 +38,11 @@ When interacting with the MCP server via HTTP requests, follow this initializati
1. **The client sends an `initialize` request** with protocol version and capabilities.
2. **The server replies with an `initialize` response**, including the supported protocol and capabilities.
3. **The client confirms readiness with an `initialized` notification**.
3. **The client confirms readiness with an `initialized` notification**.
_The connection is established between the client and the server, and further operations (such as tool listing) may proceed._
:::tip NOTE
For more information about this initialization process, see [here](https://modelcontextprotocol.io/docs/concepts/architecture#1-initialization).
For more information about this initialization process, see [here](https://modelcontextprotocol.io/docs/concepts/architecture#1-initialization).
:::
In the following sections, we will walk you through a complete tool calling process.

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@ -5,7 +5,6 @@ sidebar_custom_props: {
categoryIcon: LucideToolCase
}
---
# RAGFlow MCP tools
The MCP server currently offers a specialized tool to assist users in searching for relevant information powered by RAGFlow DeepDoc technology: