MCP server

BlockWerk Official

tech.blockwerk/mcp

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Build, run and analyse block-diagram simulations: PID, Bode, FFT, optimisation and code export.

Website

At a glance

Type

MCP server

Publisher

blockwerk.tech (verified by the MCP Registry)

Status

Working at last check

Tools

42

Token cost

About 6,589 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http blockwerk https://blockwerk-mcp-worker.blockwerk.workers.dev/

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.blockwerk]
url = "https://blockwerk-mcp-worker.blockwerk.workers.dev/"

Gemini CLI

{"mcpServers":{"blockwerk":{"httpUrl":"https://blockwerk-mcp-worker.blockwerk.workers.dev/"}}}

Cursor

{"mcpServers":{"blockwerk":{"url":"https://blockwerk-mcp-worker.blockwerk.workers.dev/"}}}

VS Code

{"servers":{"blockwerk":{"type":"http","url":"https://blockwerk-mcp-worker.blockwerk.workers.dev/"}}}

Antigravity

agy mcp add blockwerk https://blockwerk-mcp-worker.blockwerk.workers.dev/

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"blockwerk","server_url":"https://blockwerk-mcp-worker.blockwerk.workers.dev/","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"blockwerk","server_url":"https://blockwerk-mcp-worker.blockwerk.workers.dev/"}

Tools

• add_block ~140 tokens
  Add a new block to the canvas. Returns the new block ID.
• analyze_topology ~68 tokens
  Analyzes the block diagram structure: detects feedback loops, signal paths, and system order.
• auto_tune_pid ~278 tokens
  Automatically tunes a PID controller using the Ziegler-Nichols ultimate cycle method. Finds the ultimate gain (Ku) and oscillation period (Tu) via binary search, then applies ZN formulas. No prior knowledge of the plant required.
• batch_commands ~447 tokens
  Executes multiple canvas manipulation and background job commands in a single round-trip. Use "handle" strings to refer to blocks added earlier in the same batch. When adding TextNote annotations, set "anchors" to the handles/IDs of the described blocks so auto-layout keeps each note next to them.
• calculate_metrics ~125 tokens
  Calculates step response metrics from signal data: rise time, settling time, overshoot percentage, and steady-state error.
• cancel_job ~62 tokens
  Cancel a running background job.
• clear_canvas ~79 tokens
  Remove all blocks and connections from the canvas. This is a destructive action that asks the user for approval in the BlockWerk tab.
• connect_blocks ~249 tokens
  Connect an output port of one block to an input port of another. Automatically resolves common port aliases (e.g., "in" -> "signal" for uPlotDisplay, "in" -> "error" for PIDController, "+" / "-" for Subtraction).
• delete_block Deletes data · ~106 tokens
  Delete a block and all its connections from the canvas. This is a destructive action that asks the user for approval in the BlockWerk tab.
• describe_canvas ~115 tokens
  Returns a structured description of all blocks and connections currently on the canvas. Set "compact" to true for a token-efficient summary.
• evaluate_spec_mask ~288 tokens
  Evaluates signal data against automated design specifications and tolerance corridors (rise time, settling time, overshoot %, steady-state error, min/max limits).
• explain_simulation ~215 tokens
  Analyze the last completed simulation and return a structured diagnosis: signal anomalies (NaN, divergence, oscillation), solver health (rejection rate, efficiency), algebraic loops, and optional stability margins. Returns JSON with severity-tagged findings and actionable suggestions.
• export_diagram ~62 tokens
  Exports the current canvas project as a complete BlockWerk JSON string.
• generate_code ~248 tokens
  Generates standalone production code (C++, Python, Rust) from the current canvas diagram. Returns structured code files, interfaces (inputs/outputs), execution order, and diagnostics.
• get_ai_history ~68 tokens
  Returns the list of recent canvas operations performed by the AI, showing what can be undone.
• get_analysis_measurements ~102 tokens
  Retrieves the currently active pinned measurements and their computed values across plotted signals in the Analysis panel.
• get_architect_memory ~58 tokens
  Returns the persistent memory object of the Architect.
• get_available_blocks ~250 tokens
  Returns the block types in the library with their descriptions, configurable parameters, and exact input/output port IDs. Without a filter it returns a compact list of all types; with a list of type IDs it returns full details for those types. Example port IDs: Step out "out"; Sum in "in", out "out"
• get_bode_data ~238 tokens
  Computes magnitude and phase frequency response (Bode data) between two blocks. Traces path backwards from outputBlockId. Returns analytic response if the path contains only linear blocks, otherwise runs numerical sweep.
• get_canvas_preview ~142 tokens
  Captures a visual screenshot preview of the canvas branded with the official BlockWerk watermark badge and returns the live interactive URL to view and edit the diagram online.
• get_engine_status ~78 tokens
  Returns the simulation engine status, including supported solvers, active background jobs, and compilation/WASM capabilities.
• get_fft_data ~111 tokens
  Computes FFT (frequency spectrum) of a Scope signal. Returns frequencies and magnitudes.
• get_job_status ~69 tokens
  Check the status and progress of a background job.
• get_share_link ~114 tokens
  Returns a link that opens the current diagram on the BlockWerk canvas. The whole project travels compressed inside the URL, so it needs no account and nothing is uploaded. Opening the link in a browser shows the diagram, where the simulation can be run.
• get_signal_data ~105 tokens
  Returns time series data from a Scope block output for analysis.
• get_templates ~226 tokens
  Lists the built-in, verified BlockWerk diagrams: classic control systems (PID loop, cruise control, inverted pendulum), signal processing, electrical and physics models. Each entry gives an id, what the diagram does, its difficulty and the blocks it uses. Returns metadata only; load_template puts a
• identify_fopdt ~202 tokens
  Analyzes a step response from a plant to identify its First-Order Plus Dead Time (FOPDT) parameters: Gain (K), Time Constant (tau), and Dead Time (theta). Requires a completed simulation with a step input connected to the plant. Returns the calculated parameters.
• list_jobs ~54 tokens
  List all recent background jobs and their status.
• load_diagram ~304 tokens
  Atomically replaces the entire canvas with a complete diagram defined as a BlockWerk project JSON string. The JSON has a "blocks" array (each block needs a unique "id" and "type"; "x"/"y"/"params" are optional) and a "connections" array (each connection needs a unique "id" plus "fromBlockId", "fromP
• load_template ~196 tokens
  Replaces the entire canvas with one of the built-in verified diagrams, by id from get_templates. The template carries its topology, parameters and simulation settings. Returns the block and connection counts, the verified simulation settings, and the attribution when the model is based on third-part
• optimize_multi_parameter ~287 tokens
  Optimizes 2–6 parameters simultaneously using Nelder-Mead simplex search, for example Kp, Ki and Kd of a PID controller at once.
• optimize_parameters ~334 tokens
  Finds the optimal value for a single parameter using golden-section search. Minimizes IAE (integral absolute error), overshoot, or settling_time within a [min, max] range. Converges in about 10 simulations.
• redo_last_ai_action ~55 tokens
  Redoes the last undone canvas modification.
• run_simulation ~160 tokens
  Triggers a new simulation run with the current canvas state and settings, refreshing the signal data.
• start_optimization ~155 tokens
  Start a parameter optimization job in the background.
• sweep_parameter ~242 tokens
  Runs simulations across a list of values for one parameter, returning control quality metrics (IAE, overshoot, settling_time, steady_state_error) per value. Requires measureBlockId and setpoint.
• tidy_layout ~64 tokens
  Automatically rearrange all blocks on the canvas into a clean, left-to-right flow.
• undo_last_ai_action ~71 tokens
  Undoes the last canvas modification made by the AI (add block, connect, delete, update parameter).
• update_architect_memory ~114 tokens
  Updates the persistent memory of the Architect. Provide a JSON object with keys to update/merge.
• update_params ~130 tokens
  Update one or more parameters of an existing block.
• validate_canvas ~100 tokens
  Performs pre-flight topological and numerical integrity checks on the canvas. Detects unconnected required input ports, isolated blocks, parameter domain anomalies, and direct algebraic feedthrough loops.
• validate_engineering_units ~78 tokens
  Checks the consistency of engineering units across the diagram. Detects incompatible connections and missing units.

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