Control ParaView visualizations, execute Python code, and capture screenshots via MCP.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
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π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Connect ParaView to LLM assistants through the Model Context Protocol.
The Python server is built with FastMCP 3.x. Support for the
2026-07-28 MCP specification is planned once FastMCP 4 reaches a stable release.
paraview-mcp-server has two runtime parts:
First set up the ParaView plugin. Then add the Python MCP server to Claude Code in one command:
Open Tools > ParaView MCP in ParaView, start the bridge, and connect from Claude Code.
Download a pre-built plugin binary from the latest GitHub Release. Releases provide this matrix:
| Platform | Architecture | ParaView versions | Package |
|---|---|---|---|
| Linux | x86_64 | 5.13.3, 6.0.1, 6.1.1 | .tar.gz |
| macOS | arm64 (Apple Silicon) | 5.13.3, 6.0.1, 6.1.1 | .dmg |
| Windows | x64 | 5.13.3, 6.0.1, 6.1.1 | .zip |
Choose the package that names your exact ParaView version and platform. Download its
adjacent .sha256 file, verify the package, then open or extract it and follow the
included INSTALL.md. Pull requests also produce corresponding platform binaries as
short-lived GitHub Actions artifacts; GitHub Releases are the permanent distribution
channel.
macOS release images are Developer ID-signed, notarized by Apple, and include a stapled
notarization ticket. Open the .dmg, copy the contained plugin directory to a persistent
location, and load ParaViewMCP.so from that copied directory. Pull-request artifacts are
unsigned test builds and remain .tar.gz files.
Alternatively, build the plugin from source against a ParaView 5.13 or newer SDK. See CONTRIBUTING.md for full build instructions. Binary compatibility is release-series specific, so use a plugin built for your ParaView major.minor version.
Once installed:
ParaViewMCP.so (Linux/macOS) or ParaViewMCP.dll (Windows) from the plugin directory.The ParaView MCP panel shows the connection status and execution history. Non-loopback binds require an auth token.
Add to your claude_desktop_config.json:
Configure a local stdio MCP server with uvx as the command and
paraview-mcp-server as its only argument:
Consult your client's documentation for the location and exact format of its MCP server configuration.
The server connects to the ParaView plugin using these environment variables:
| Variable | Default | Required | Description |
|---|---|---|---|
PARAVIEW_HOST | 127.0.0.1 | No | Host where the ParaView plugin is listening |
PARAVIEW_PORT | 9877 | No | TCP port for the plugin bridge |
PARAVIEW_AUTH_TOKEN | β | Non-loopback only | Authentication token (must match the plugin setting) |
PARAVIEW_CONNECT_TIMEOUT_SECONDS | 30 | No | Deadline for opening the connection and completing the hello |
PARAVIEW_COMMAND_TIMEOUT_SECONDS | β | No | Optional deadline for receiving a command result |
Defaults work for a standard local setup. Override these when connecting to ParaView on a remote machine or non-standard port:
| Tool | Description |
|---|---|
execute_paraview_code(code) | Execute Python code inside the active ParaView session |
get_pipeline_info() | Return a JSON snapshot of the current pipeline |
get_screenshot(width, height) | Capture the active render view as a PNG image |
ParaView commands are serialized because the live ParaView session is not safe to
mutate concurrently. One command runs while up to three additional commands wait in
FIFO order. A cancelled waiting call is removed without reaching ParaView. Further
execute_paraview_code calls return request_status: "busy" with
execution_status: "not_started"; the other tools report a PARAVIEW_BUSY tool error.
execute_paraview_code reports request delivery separately from Python execution. A
completed request can therefore return execution_status: "failed" together with
Python stderr, a traceback, ParaView/VTK diagnostics, and execution duration. Command
diagnostics are process-global events observed while the command runs, which the
paraview_diagnostics_scope field states explicitly. Command results have no deadline
by default so long computations can finish. If
PARAVIEW_COMMAND_TIMEOUT_SECONDS is set and expires, the result is
request_status: "outcome_unknown"; do not retry the command automatically because it
may already have modified the ParaView session. The server then rejects queued and
future commands with request_status: "recovery_required" until the MCP server is
restarted. This prevents new work from overlapping the still-running command or using a
silently reset session. The original success field remains available for existing
clients and is true only for completed and succeeded results.
This project follows the approach of Blender-MCP and Slicer-MCP, both of which give LLMs direct code execution inside their respective application runtimes.
The existing ParaView_MCP implementation1 takes a different approach, exposing a fixed set of high-level tools without access to the underlying Python runtime, which limits flexibility for custom workflows. The major differences are:
execute_paraview_code tool that runs arbitrary Python inside the
ParaView session. The plugin records each execution and, when ParaView can capture a
pipeline snapshot, lets the user restore the state from immediately before that
execution. This makes generated scripts easier to inspect, reuse, and adapt for tasks
such as batch processing.pvserver and the ParaView client.
That synchronization mechanism is deprecated in recent ParaView versions and can
cause incorrect application views and general stability issues. This project instead
runs a plugin inside the interactive ParaView process and exposes a TCP bridge,
avoiding the pvserver/client synchronization path entirely.See CONTRIBUTING.md for build instructions, development setup, and pull request guidelines.
MIT β see THIRD-PARTY-NOTICES.txt for dependency licenses.
S. Liu, H. Miao, and P.-T. Bremer, "Paraview-MCP: Autonomous Visualization Agents with Direct Tool Use," in Proc. IEEE VIS 2025 Short Papers, IEEE, 2025. β©
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