dcc-mcp-renderdoc
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@dcc-mcp-renderdoccapture a single frame from myApp.exe"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
dcc-mcp-renderdoc
Agent workflow
AI agents should use the shared gateway through dcc-mcp-cli; IDE users may
continue to use the MCP endpoint. Prefer typed skills and tools over raw scripts.
Install or update the CLI
dcc-mcp-cli is the preferred control path for every shell-capable agent. If
it is missing, ask the user before installing the latest official release:
# Linux/macOS
curl -fsSL https://raw.githubusercontent.com/dcc-mcp/dcc-mcp-core/main/scripts/install-cli.sh | sh
# Windows PowerShell
powershell -ExecutionPolicy Bypass -c "irm https://raw.githubusercontent.com/dcc-mcp/dcc-mcp-core/main/scripts/install-cli.ps1 | iex"Keep an official build current through the release manifest:
dcc-mcp-cli update check
dcc-mcp-cli update applyupdate apply downloads and stages the latest CLI for the next launch. It
does not update a running dcc-mcp-server; update that server in its own
environment.
dcc-mcp-cli dcc-types
dcc-mcp-cli list
dcc-mcp-cli search --query "<task>" --dcc-type renderdoc
dcc-mcp-cli describe <tool-slug>
dcc-mcp-cli call <tool-slug> --json '{"key":"value"}'dcc-types reports release-catalog support; list reports live sessions. If a
tool belongs to an inactive progressive skill, call dcc-mcp-cli load-skill <skill-name> --dcc-type renderdoc before retrying. For post-task improvement,
attach a stable session id with --meta-json, query dcc-mcp-cli stats --range 24h --session-id <task-id>, then pass the bounded evidence to the
review_skill_improvement prompt from dcc-mcp-skills-creator.
RenderDoc capture and replay automation for the DCC Model Context Protocol ecosystem.
The adapter is headless-first: it reuses the official renderdoccmd executable for capture and
conversion. Delayed capture uses RenderDoc's official Target Control API through the sibling
qrenderdoc bundled Python runtime, without foreground focus or synthetic keyboard input.
Related MCP server: RenderDoc MCP Server
Install
pip install dcc-mcp-renderdocInstall RenderDoc separately, then expose its command line tool with either PATH or:
export DCC_MCP_RENDERDOC_CMD=/opt/renderdoc/bin/renderdoccmd
dcc-mcp-renderdocOn Windows, set the variable to renderdoccmd.exe.
Each adapter instance uses an OS-assigned MCP port and registers it for CLI discovery. Connect
through the stable gateway at http://127.0.0.1:9765/mcp; set
DCC_MCP_RENDERDOC_PORT only when a fixed direct endpoint is required.
Agent workflows
Launch a game or test executable under RenderDoc and wait for a typed
.rdccapture.Trigger a capture through official Target Control after a configurable delay.
Inject into a process that had to be launched by a platform client, then trigger and collect a capture.
Reject no-work captures with actionable diagnostics while preserving the
.rdcartifact.Inspect capture driver, machine identity, chunk version, frame-work and Present counts, and representative calls.
Export a capture thumbnail for visual review.
Export Chrome trace JSON for timeline tooling.
The capture tool launches only the explicit executable and arguments supplied by the caller. It
never invokes a shell. Analysis tools are read-only with respect to the .rdc input.
Pass trigger_after_secs to capture_program for a Target Control trigger. This requires
qrenderdoc beside renderdoccmd. The official RenderDoc runtime supports Windows and Linux;
macOS is covered only by this project's Python unit tests. Linux Target Control requires an X or
Wayland display, so headless hosts must run under Xvfb (or explicitly configure a working Qt
platform). The official Linux archive does not bundle Qt's offscreen platform plugin. Each
sidecar uses an isolated Qt data profile with RenderDoc analytics explicitly opted out, preventing
the first-run consent dialog without reading or changing the user's qrenderdoc configuration.
When a launcher creates the rendered child process, set hook_children=true and pass
trigger_process_name. The adapter first checks the launched target itself; if its name does not
match, it follows only that target's official NewChild messages to find a unique named child. A
child name without child hooking fails before launch. Use capture_process only when the target is
already running; late injection may not capture graphics devices created before RenderDoc was
attached.
Real CI
CI discovers the current stable Linux RenderDoc build from the official downloads page. It
compiles a small OpenGL program, requests a real frame through Target Control under Xvfb using
Qt's bundled xcb platform, asserts the structured trigger mode, calls the MCP analysis tool
against the resulting .rdc, and verifies thumbnail and timeline exports.
Development
uv sync --extra dev
uv run python -m pytest
uv run ruff check src tests tools
uv run python tools/lint_skills.pyRenderDoc is an MIT-licensed graphics debugger maintained independently at renderdoc.org. This adapter is not affiliated with the RenderDoc project.
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Maintenance
Resources
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Looking for Admin?
If you are the server author, to access and configure the admin panel.
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