opm-mcp

opm-mcp

Provides Claude with direct access to the Open Porous Media (OPM) reservoir simulation stack, enabling running simulations, inspecting results, and automating workflows via natural language.

Category
访问服务器

README

opm-mcp

CI License: MIT Python 3.11+ MCP

A Model Context Protocol (MCP) server that gives Claude direct access to the Open Porous Media reservoir-simulation stack:

  • OPM Flow — black-oil and compositional reservoir simulator (ECLIPSE-compatible), from OPM/opm-simulators.
  • ResInsight — 3D viewer and post-processor.
  • OPM utility binariesopmpack, opmhash, summary, convertECL, compareECL.
  • OPM upscaling (optional opm-upscaling package).

flow and its Python bindings (python3-opm-simulators) are built from the OPM/opm-simulators repository — see it for the simulator source, supported keywords, build instructions, and issue tracker.

The server runs on Windows so Claude Code / Claude Desktop can spawn it natively, but it delegates every Linux-only binary to an Ubuntu distro under WSL2. Result files (UNSMRY / UNRST / EGRID / INIT) are parsed natively on Windows via resdata.

Architecture

   +-------------------+              +----------------------+
   |     Windows       |              |   WSL2 Ubuntu-24.04  |
   |                   |              |                      |
   |  Claude  <----->  |   wsl.exe    |   flow               |
   |  opm-mcp (Py)     | -----------> |   ResInsight         |
   |     resdata       |              |   python3-opm-common |
   |     (UNSMRY etc.) |              |   convertECL/etc.    |
   +-------------------+              +----------------------+
            ^                                       |
            |     reads result files via UNC /      |
            +---  /mnt/c/... path translation  -----+

Prerequisites

On Windows:

  • Python 3.11+ (tested with 3.13).
  • WSL2 enabled, with an Ubuntu-24.04 distro available (wsl -l -v).

In the WSL distro, install OPM:

sudo apt-get update
sudo apt-get install flow resinsight python3-opm-common python3-opm-simulators
# Optional, for the upscaling tools:
sudo apt-get install opm-upscaling
# Optional, for fully headless ResInsight rendering without WSLg:
sudo apt-get install xvfb mesa-utils libgl1-mesa-dri

The flow simulator comes from OPM/opm-simulators. The apt packages above track upstream releases; to run a development build or a specific version, follow the build instructions there and point the server at it with OPM_MCP_FLOW_BIN (see Configuration).

Install

git clone https://github.com/ojaogezi/opm-mcp.git
cd opm-mcp
py -m pip install -e .

This installs the opm-mcp console script and pulls in mcp[cli], resdata, pydantic and numpy.

For development:

py -m pip install -e ".[dev]"
pytest

Register with Claude Code

claude mcp add opm --scope user -- py -m opm_mcp.server

Or, if you prefer a JSON config (Claude Desktop / cursor / etc.), add this to your mcpServers block:

{
  "mcpServers": {
    "opm": {
      "command": "py",
      "args": ["-m", "opm_mcp.server"],
      "env": {
        "OPM_MCP_WSL_DISTRO": "Ubuntu-24.04"
      }
    }
  }
}

Configuration (env vars)

Variable Default Purpose
OPM_MCP_WSL_DISTRO Ubuntu-24.04 Name of the WSL distro to run OPM in.
OPM_MCP_FLOW_BIN flow Binary name / absolute WSL path for Flow.
OPM_MCP_RESINSIGHT_BIN ResInsight Binary name / absolute WSL path for ResInsight.
OPM_MCP_WORK_DIR ~/.opm-mcp (Win) Where job logs and artefacts go.
OPM_MCP_FLOW_THREADS 0 (auto) --threads-per-process default for runs.
OPM_MCP_JOB_HISTORY 50 How many recent jobs to remember in-memory.
OPM_MCP_LOG_TAIL 200 Default line count for flow_log_tail.

Tool reference

Environment & paths

Tool Purpose
opm_environment Probe wsl.exe, flow, ResInsight, OPM Python bindings.
to_wsl_path Translate C:\foo\bar to /mnt/c/foo/bar.
to_windows_path Reverse translation.

Deck inspection (uses python3-opm-common in WSL)

Tool Purpose
validate_deck Parse a DATA deck, report keyword counts.
summarize_deck Phases, units, grid dims, well/group counts, schedule length.
list_wells Per-well info at schedule step 0.

OPM Flow (background jobs)

Tool Purpose
run_flow Start a Flow job; returns a job_id immediately.
flow_status Current state + last progress line (Report step N/M ...).
flow_log_tail Tail of combined stdout/stderr.
flow_cancel Cancel a running job.
flow_jobs List recent jobs (most recent first).

Result readers (native Windows via resdata)

Tool Purpose
list_summary_vectors All summary keys (FOPR, WBHP:, GOPR:, ...).
read_summary Time series for one or more keys, with per-vector units + elapsed days, downsampled.
field_summary Cumulative production/injection, FPR, final rates (with units).
well_summary Per-well WOPR/WGPR/WWPR/WBHP/WOPT/etc. min/max/last.
grid_info EGRID dims, active count, INIT property stats.
restart_info UNRST report step list + keywords.
compare_summaries Diff field totals between two cases.

Native plotting (matplotlib — no ResInsight/OpenGL)

Tool Purpose
plot_summary Render summary vectors to a PNG, auto twin-axis by unit, date or days x-axis. The fast path for rate/pressure/cumulative plots.

Reservoir-engineering analytics

Tool Purpose
material_balance_check OOIP, recovery factor, exact oil mass-balance drift, surface VRR.
flow_convergence_report Parse INFOSTEP/INFOITER: wall time by stage, wasted (cut) steps, worst timesteps, residuals.
restart_property Per-layer stats (PV-weighted when INIT present) for PRESSURE/SWAT/SGAS/SOIL at a report step, plus histogram.

For PVT, SCAL/relative-permeability fitting and deck-physics validation, this server defers to the pyrestoolbox MCP if you have it connected, rather than duplicating those calculators.

Deck editing (sensitivities / history matching)

Tool Purpose
clone_deck Write a NEW deck with safe overrides (append_before_end, replace_regex, set_title, insert_after_keyword), reporting per-op substitution counts and re-validating. Enables clone → run → compare loops.

ResInsight automation (CLI command files)

Tool Purpose
resinsight_snapshot Open a case, render the default 3D view, save PNG.
resinsight_well_log Export an LAS well log for one well.
resinsight_open Launch interactive ResInsight (uses WSLg on Windows 11).

If ResInsight fails with MESA: error: ZINK ..., pass force_software_gl: true or install xvfb and libgl1-mesa-dri in WSL.

OPM utility binaries

Tool Purpose
convert_ecl Toggle formatted/unformatted ECL output files.
compare_ecl Diff two result files within tolerances.
pack_deck Flatten a deck + INCLUDEs into one file (opmpack).
hash_deck Keyword-level deterministic hash (opmhash).
summary_tool Text summary table via the OPM summary CLI.
upscaling_status Detect whether opm-upscaling is installed in WSL.
run_upscaling Generic passthrough to upscale_perm, upscale_relperm, ...

Bigger test cases

This repo only ships the tiny examples/SPE1_MINI.DATA. For real benchmark decks (Norne, SPE9, SPE10, Equinor gas-lift demos, etc.) use the upstream OPM/opm-tests repository — they're distributed under the Open Database License (ODbL 1.0) and shouldn't be re-vendored here. Clone alongside:

git clone https://github.com/OPM/opm-tests.git C:\models\opm-tests

Then point the MCP tools at any deck under that tree, e.g. C:\models\opm-tests\norne\NORNE_ATW2013.DATA.

Smoke test

# 1. Validate a small example deck
py -c "from opm_mcp.tools import deck; import json; print(json.dumps(deck.summarize_deck(r'C:\Users\ogezi\RCI\opm-mcp\examples\SPE1_MINI.DATA'), indent=2))"

# 2. Run Flow on it (completes in a couple of seconds)
py -c "from opm_mcp.tools import flow; import time, json; j = flow.run_flow(r'C:\Users\ogezi\RCI\opm-mcp\examples\SPE1_MINI.DATA'); print(j['job_id']);
import time
time.sleep(5)
print(json.dumps(flow.flow_status(j['job_id']), indent=2))"

# 3. Read summary vectors
py -c "from opm_mcp.tools import results as r; import json; print(json.dumps(r.field_summary(r'C:\Users\ogezi\.opm-mcp\jobs\<JOB_ID>\out\SPE1_MINI'), indent=2))"

Project layout

opm-mcp/
  pyproject.toml
  README.md
  examples/
    SPE1_MINI.DATA
  src/opm_mcp/
    __init__.py
    config.py            # env-var driven settings
    wsl.py               # WSL bridge + path translation (wslpath-aware)
    jobs.py              # background flow-job tracker (restart-safe)
    server.py            # FastMCP entry point (`opm-mcp` script)
    tools/
      deck.py            # validate / summarise / wells
      flow.py            # run, status, log_tail, cancel, jobs
      results.py         # resdata-backed summary/grid/restart readers (units + cache)
      plots.py           # native matplotlib plot_summary
      analysis.py        # material balance, convergence report, restart property
      edit.py            # clone_deck with safe overrides
      resinsight.py      # snapshot, well log, interactive open
      utils.py           # opmpack, opmhash, summary, compareECL, upscaling
    helpers/
      deck_inspect.py    # runs inside WSL — uses python3-opm-common

Notes

  • Path handling. Every path argument can be Windows-style (C:\\foo) or WSL-style (/mnt/c/foo, /home/...); the server normalises both directions. Result-file tools accept either the bare case name (SPE1_MINI) or any of its known extensions (.DATA, .SMSPEC, .EGRID, .UNRST).
  • Background simulations. run_flow returns immediately and writes its Linux PID + exit code under OPM_MCP_WORK_DIR/jobs/<id>/. Jobs are rehydrated on server restart, so you can still poll (and cancel, via wsl kill) a run that was started before Claude Desktop restarted. Runs also emit INFOSTEP/INFOITER by default for flow_convergence_report.
  • Optional upscaling. The opm-upscaling Debian package is not a dependency of Flow; upscaling_status tells Claude whether it's available and prints the install command if not.

License

MIT — see LICENSE for the full text.

Acknowledgements

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选