renderdoc-mcp

renderdoc-mcp is an MCP (Model Context Protocol) server that uses RenderDoc’s headless Python replay API to analyze GPU frame capture files (.rdc). It exposes many MCP tools for session/capture management, event navigation, pipeline/shader inspection, resource export/extraction, pixel diagnostics, and performance/pass analysis.

Evaluated Mar 30, 2026 (0d ago)
Repo ↗ DevTools mcp renderdoc graphics-debugging gpu-capture python headless tooling diagnostics
⚙ Agent Friendliness
67
/ 100
Can an agent use this?
🔒 Security
20
/ 100
Is it safe for agents?
⚡ Reliability
26
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
88
Documentation
80
Error Messages
0
Auth Simplicity
95
Rate Limits
10

🔒 Security

TLS Enforcement
0
Auth Strength
20
Scope Granularity
0
Dep. Hygiene
50
Secret Handling
40

No TLS/auth/authz model described (likely intended for local usage). It requires a local RenderDoc module path and reads/exports capture-derived data; the README does not discuss input sanitization, sandboxing, file-write permissions, or redaction of sensitive data contained in captures. Dependency hygiene and CVE posture cannot be determined from provided content.

⚡ Reliability

Uptime/SLA
0
Version Stability
35
Breaking Changes
40
Error Recovery
30
AF Security Reliability

Best When

You have local RenderDoc installed, can point the MCP server to the RenderDoc module, and want an AI agent to drive systematic, reproducible analysis of captured frames in a headless workflow.

Avoid When

You need a hosted API with robust authentication, rate limiting, and operational guarantees; this project appears to be a local developer tool rather than a managed service.

Use Cases

  • AI-assisted debugging of graphics issues from .rdc captures (pipeline/blend/depth/stencil/shader state)
  • Automated identification of render passes, draw-call differences, and potential state-change/batching optimizations
  • Texture/pixel/RT anomaly detection (NaN/Inf/negative hotspots) and per-pixel history investigation
  • Mobile/GPU quirk and precision-mismatch risk diagnostics
  • Headless batch export of textures/render targets/meshes for further offline analysis

Not For

  • Real-time capture analysis without pre-existing .rdc files
  • Production-grade, multi-tenant, internet-facing services requiring strong auth and TLS termination
  • Environments where the RenderDoc replay module cannot be loaded (missing renderdoc.pyd/renderdoc.so)
  • Workloads needing strict PII/secret redaction guarantees (no explicit redaction policy documented)

Interface

REST API
No
GraphQL
No
gRPC
No
MCP Server
Yes
SDK
No
Webhooks
No

Authentication

Methods: No authentication mechanism documented; intended for local MCP client/server usage
OAuth: No Scopes: No

No auth, API keys, or user-level access control described in the README; MCP server appears intended to run locally and be controlled by the configured MCP client.

Pricing

Free tier: No
Requires CC: No

No pricing information provided; repository appears to be an open-source tool.

Agent Metadata

Pagination
none
Idempotent
False
Retry Guidance
Not documented

Known Gotchas

  • Requires RenderDoc Python module (renderdoc.pyd/renderdoc.so) and correct RENDERDOC_MODULE_PATH; tool execution may fail if the module path is wrong.
  • Some event/pipeline queries likely require navigation via set_event before calling pipeline/detail tools (README notes set_event is required before pipeline queries).
  • Large exports (batch texture export, pixel history) may be slow/heavy; no rate limiting or workload guidance documented.
  • Captures are stateful per session (open_capture auto-closes previous capture); agents should manage session lifecycle carefully (open->analyze->close).

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Scores are editorial opinions as of 2026-03-30.

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