audio_fingerprint_to_visual
Sample a few seconds of audio inside TouchDesigner, compute a 4-feature fingerprint (tempo, spectral centroid, onset density, dynamic range), run a deterministic heuristic mapping to pick a matching Layer 1 generator (create_glitch / create_audio_reactive / create_kaleidoscope / create_feedback_t...
This record as markdown: /tools/io-github-pantani-tdmcp/audio-fingerprint-to-visual.md
What audio_fingerprint_to_visual does on tdmcp — TouchDesigner MCP server
AI agents invoke audio_fingerprint_to_visual to trigger actions in tdmcp — TouchDesigner MCP server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why audio_fingerprint_to_visual is rated High
This tool performs code execution and procedural generation within TouchDesigner based on audio input analysis. While it doesn't delete data (not Destructive), doesn't move money (not Financial), and doesn't simply retrieve data (not Read), it actively executes logic that creates visual generators and modifies the TouchDesigner project state.
From the tool's definition The tool description explicitly states it will 'compute', 'run a deterministic heuristic mapping', 'pick a matching Layer 1 generator', and 'dispatch it with parameters'.
Attacks that exploit this kind of access
The rule that runs audio_fingerprint_to_visual safely
PolicyLayer is an MCP gateway: it sits between your AI agents and tdmcp — TouchDesigner MCP server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For audio_fingerprint_to_visual, this is the rule to start with:
audio_fingerprint_to_visual stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect tdmcp — TouchDesigner MCP server, apply this rule, and every audio_fingerprint_to_visual call is checked against it from then on.
Questions about audio_fingerprint_to_visual
Sample a few seconds of audio inside TouchDesigner, compute a 4-feature fingerprint (tempo, spectral centroid, onset density, dynamic range), run a deterministic heuristic mapping to pick a matching Layer 1 generator (create_glitch / create_audio_reactive / create_kaleidoscope / create_feedback_tunnel / create_feedback_network / create_gpu_particle_field), and dispatch it with parameters tuned to the fingerprint. Default audio_source=. It is categorised as a Execute tool in the tdmcp — TouchDesigner MCP server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the tdmcp — TouchDesigner MCP server MCP server in PolicyLayer and add a rule for audio_fingerprint_to_visual: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches tdmcp — TouchDesigner MCP server. Nothing to install.
audio_fingerprint_to_visual is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the audio_fingerprint_to_visual rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for audio_fingerprint_to_visual. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
audio_fingerprint_to_visual is provided by the tdmcp — TouchDesigner MCP server MCP server (@dpantani/tdmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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