puran-water/dexpi-sfiles-mcp-server

Engineering MCP Server

⚠️ DEVELOPMENT STATUS: This project is under active development and is not yet production-ready. APIs, interfaces, and functionality may change without notice. Use at your own risk for evaluation and testing purposes only. Not recommended for production deployments.

Structured P&ID and Flowsheet Generation for LLM Agents

The Engineering MCP Server exposes pyDEXPI (DEXPI P&IDs) and SFILES2 (BFD/PFD flowsheets) through Anthropic's Model Context Protocol so language-model agents can create, modify, analyze, and persist process-engineering diagrams entirely in machine-readable formats.

This repository prioritizes data fidelity over drawing aesthetics: the authoritative artifacts are JSON/SFILES models tracked in git, with optional Plotly-based HTML visualizations and GraphML exports generated from the same state.

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Current Capabilities

• Complete pyDEXPI Coverage (Phase 2) – All 272 pyDEXPI classes are now accessible: 159 equipment types, 79 piping types, and 34 instrumentation types. Both SFILES aliases (e.g., pump, heat_exchanger) and DEXPI class names (e.g., CentrifugalPump, PlateHeatExchanger) are accepted. See for the complete catalog and for usage guidance.
• Symbol Mapping (Phase 3) – 308/805 symbols mapped (38.3% coverage) with DEXPI class mappings from NOAKA/DISC symbol libraries.
• Proteus XML 4.2 Export – Comprehensive pyDEXPI → Proteus XML exporter with complete attribute coverage. Exports equipment, piping (with CenterLine geometry), instrumentation (with actuating functions and signal connectors), nozzle connection points, and GenericAttributes. Features "fail loudly" validation with clear error messages. See for implementation details. 45/45 tests passing with XSD validation and round-trip fidelity verified.
• DEXPI P&ID tooling – 14 MCP tools for creating models, adding equipment/piping/instrumentation, importing/exporting, and inserting inline valves (src/tools/dexpi_tools.py).
• SFILES BFD/PFD tooling – 12 MCP tools for flowsheet construction, stream management, canonicalization, regex validation, and conversions from/to DEXPI (src/tools/sfiles_tools.py).
• Git-native persistence – Project tools (project_init/save/load/list) wrap src/persistence/project_persistence.py, storing JSON/SFILES plus metadata, GraphML, and Plotly HTML in per-model folders with automatic commits.
• Template deployment – template_list, template_get_schema, and area_deploy expose four YAML templates (library/patterns/*.yaml): pump_basic, pump_station_n_plus_1, tank_farm, and heat_exchanger_with_integration.
• Validation & analytics – Schema introspection (schema_*), validation (validate_model, validate_round_trip), graph analytics (graph_*), search (search_*, query_model_statistics), and batch automation (model_batch_apply, rules_apply, graph_connect).
• Visualization outputs – Project saves produce Plotly-based interactive HTML files (with SVG/PDF exports via Plotly's toolbar) and GraphML topology exports. GraphicBuilder integration provides production-quality PNG rendering from Proteus/DEXPI XML (validated with official DEXPI TrainingTestCases). There is no standalone dashboard service; visual review happens through the generated HTML files.
• Phase 4 Tool Consolidation – 7 unified tools (model_create, model_load, model_save, model_combine, model_tx_begin, model_tx_apply, model_tx_commit) provide ACID transaction support alongside 71 domain-specific tools (78 total). See for the migration guide.

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MCP Tool Catalog (as registered in src/server.py)

DEXPI Tools

dexpi_create_pid, dexpi_add_equipment, dexpi_add_piping, dexpi_add_instrumentation, dexpi_add_control_loop, dexpi_connect_components, dexpi_validate_model, dexpi_export_json, dexpi_export_graphml, dexpi_import_json, dexpi_import_proteus_xml, dexpi_add_valve, dexpi_add_valve_between_components, dexpi_insert_valve_in_segment, dexpi_convert_from_sfiles.

SFILES Tools

sfiles_create_flowsheet, sfiles_add_unit, sfiles_add_stream, sfiles_to_string, sfiles_from_string, sfiles_export_networkx, sfiles_export_graphml, sfiles_add_control, sfiles_parse_and_validate, sfiles_canonical_form, sfiles_pattern_helper, sfiles_convert_from_dexpi, sfiles_visualize.

Project & Persistence Tools

project_init, project_save, project_load, project_list.

Validation & Schema Tools

validate_model, validate_round_trip, plus schema_list_classes, schema_describe_class, schema_find_class, schema_get_hierarchy.

Graph, Search, Batch, and Template Tools

• Graph analytics: graph_analyze_topology, graph_find_paths, graph_detect_patterns, graph_calculate_metrics, graph_compare_models.
• Search & statistics: search_by_tag, search_by_type, search_by_attributes, search_connected, query_model_statistics, search_by_stream, search_instances.
• Batch/automation: model_batch_apply, rules_apply, graph_connect.
• Templates: template_list, template_get_schema, area_deploy.

Visualization Tools (Weeks 5-6)

• visualize_model - Generate HTML (Plotly), PNG (GraphicBuilder), or GraphML from DEXPI/SFILES models with auto model-type detection and intelligent renderer selection
• visualize_list_renderers - List available renderers with capabilities and health status

Layout Tools (NEW - Week 8+)

• layout_compute - Compute automatic layout using ELK algorithm (layered, orthogonal routing)
• layout_get - Retrieve stored layout with positions, edges, ports
• layout_update - Update layout with etag-based optimistic concurrency control
• layout_validate - Validate layout schema and model consistency
• layout_list - List layouts, optionally filtered by model
• layout_save_to_file / layout_load_from_file - Persist layouts to project files
• layout_delete - Remove layout from store

Phase 4 Update: The unified tools (model_create, model_load, model_save, model_combine, model_tx_begin, model_tx_apply, model_tx_commit) provide ACID transaction support. Legacy atomic tools remain available for backward compatibility. See for migration guidance.

Layout System Update (Dec 2025): Complete Layout Layer with ELK integration. Persistent Node.js worker for efficient layout computation, etag-based concurrency control, file persistence alongside models. See for details.

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Architecture Overview

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Dependencies

Core Libraries (Pinned Versions)

This project depends on two research libraries from the Process Intelligence Research group:

These versions are pinned in pyproject.toml to ensure reproducible builds. If you need to upgrade:

1. Test with the new commit locally
2. Update the SHA in pyproject.toml
3. Update this table
4. Run full test suite (pytest tests/)

Known Upstream Issues:

• SFILES2 #12: merge_HI_nodes/split_HI_nodes bugs affect heat integration scenarios (workaround: guards in conversion code)
• SFILES2 #10: MultiDiGraph support incomplete (affects parallel edges)
• pyDEXPI: ProteusSerializer.save() is NotImplementedError (affects nozzle metadata export)

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Installation & Quick Start

1. Clone & set up environment (see for full instructions):

   git clone https://github.com/yourusername/engineering-mcp-server.git
   cd engineering-mcp-server
   python3 -m venv .venv && source .venv/bin/activate
   pip install -r requirements.txt
   

2. Validate core imports:

   python -c "from src.tools.dexpi_tools import DexpiTools; from src.tools.sfiles_tools import SfilesTools; print('OK')"
   

3. Run the MCP server:

   python -m src.server
   

4. Add to an MCP client (e.g., .mcp.json for Claude Code or Codex CLI) pointing to python -m src.server.

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Example MCP Workflow

1. Create a DEXPI P&ID using dexpi_create_pid.
2. Add equipment and piping via dexpi_add_equipment, dexpi_add_piping, and dexpi_connect_components (or batch via model_batch_apply).
3. Validate with validate_model or validate_round_trip.
4. Save to a git project:
   • project_init to scaffold pid/, pfd/, bfd/ directories.
   • project_save to persist JSON, metadata, GraphML, and Plotly HTML (commits automatically).
5. Inspect outputs by opening the generated <model>.html or <model>.graphml files in your browser/tooling of choice.

A similar flow applies to SFILES models using the sfiles_* tools and conversions between representations.

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Visualization & Data Exports

Visualization Philosophy

This system provides two complementary visualization approaches serving different purposes:

Plotly HTML (Topology Analysis)

• Purpose: Fast topology visualization for connectivity analysis and debugging
• What it shows: Network graph with nodes (equipment) and edges (connections)
• Layout: Spring/force-directed layout (automatic positioning)
• Symbols: No symbols - abstract nodes only
• Speed: <1 second generation time
• Use case: Development iteration, flow analysis, bottleneck detection
• Generated: Automatically during project_save

GraphicBuilder (Engineering Documentation)

• Purpose: Production-quality P&ID rendering for engineering deliverables
• What it shows: Proper P&ID with ISA-compliant symbols, spatial layout, annotations
• Layout: Proteus XML positioning (requires layout data)
• Symbols: Uses all 701 NOAKADEXPI symbols (from Phase 3 mapping work)
• Speed: 2-15 seconds depending on complexity
• Use case: Final documentation, compliance, client deliverables
• Generated: On-demand via GraphicBuilder Docker service
• Current Status: PNG rendering validated with DEXPI TrainingTestCases (SVG/PDF pending Java API integration)

Both approaches are complementary - Plotly for rapid iteration, GraphicBuilder for final outputs.

Data Export Formats

Symbol Library Status: 308/805 symbols mapped (38.3% coverage) from NOAKA/DISC libraries. These mappings are used by GraphicBuilder and future symbol-based renderers. Plotly visualizations do not use symbols.

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Templates

library/patterns/ currently contains four YAML templates surfaced through template_* tools:

• pump_basic.yaml
• pump_station_n_plus_1.yaml
• tank_farm.yaml
• heat_exchanger_with_integration.yaml

Each template exposes typed parameters (see template_get_schema) and can be instantiated into DEXPI or SFILES models via area_deploy.

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Development Status

For the complete development roadmap including completed phases and planned work, see .

Recent Highlights

• Phase 8: ROADMAP Audit & Quick Wins (January 2026): Added sfiles_visualize, model_combine, and search_instances tools. Layout-rendering integration with use_layout/layout_id params. Full deprecation warnings on catalog.py. See .

• Codex Deep Review (January 2026): Core conversion fixes including SFILES2 native parsing, proper piping connections, and pyDEXPI API corrections. See .

• Layout System (December 2025): Complete ELK-based automatic layout with 8 MCP tools, optimistic concurrency, and file persistence. See .

• Tool Consolidation (Phase 4): 7 unified tools with ACID transaction support alongside 71 domain-specific tools. See .

Key Documentation

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License

Released under the GNU Affero General Public License v3.0 (AGPL-3.0). See for details.