Production-shaped MCP server for Blender with goal-first routing, curated tools, deterministic verification, and vision-assisted 3D modeling workflows.
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Blender AI MCP is an MCP server that production-shaped MCP server for Blender with goal-first routing, curated tools, deterministic verification, and vision-assisted 3D modeling workflows. Its tool list has not been published yet over stdio, sse and http, requires no API key, and scores 59/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"blender-ai-mcp": {
"args": [
"run",
"-i",
"--rm",
"-v",
"/tmp:/tmp",
"-e",
"BLENDER_AI_TMP_INTERNAL_DIR=/tmp",
"-e",
"BLENDER_AI_TMP_EXTERNAL_DIR=/tmp",
"-e",
"ROUTER_ENABLED=true",
"-e",
"MCP_SURFACE_PROFILE=llm-guided",
"-e",
"BLENDER_RPC_HOST=host.docker.internal",
"ghcr.io/patrykiti/blender-ai-mcp:latest"
],
"command": "docker"
}
}
}Are you the author?
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blender-ai-mcp lets Claude, ChatGPT, Codex, and other MCP clients control Blender through a stable tool API instead of ad-hoc Python generation. The result is a safer, smaller, and more reliable surface for real modeling work: goal-first routing, curated public tools, deterministic inspection, and verification that does not depend on guesswork.
No automated test available for this server. Check the GitHub README for setup instructions.
Five weighted categories — click any category to see the underlying evidence.
No known CVEs.
No package registry to scan.
Click any tool to inspect its schema.
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