
pyeconomics
io.github.pyeconomics-devPublished by GitHub account pyeconomics-devv1.0.0b1Updated Oct 30, 2026
Tested, cited economics and finance models and data, with a provenance manifest per result.
Overview
Local MCP server exposing 50 tested, cited economics and finance model families plus a multi-provider data platform, each result with a provenance manifest.
- What you can do
- Run economics and finance models across 13 domains, including fixed income, derivatives, equity, portfolio, risk, econometrics, macroeconomics and asset pricing
- Query a data platform with 31 providers, 171 catalog concepts and live bindings with real-time vintages
- Get typed inputs with declared units and bounds, and results carrying a reproducible provenance manifest
- Export results as tables or reproducibility bundles, matching the Python API, CLI and REST surfaces
- When to use it
- Useful when an assistant needs to compute or explain finance and economics calculations with traceable, citable inputs and outputs, for example valuation, risk or macro analysis, rather than free-form estimates.
- Requirements
- Runs locally over stdio as a PyPI package, launched with uvx or installed with pip; Python 3.12 or later. The MCP extra must be installed, and the beta is a pre-release that must be requested explicitly. No authentication, environment variables or headers are declared.
Installation
In SourceWeft
- Open pyeconomics in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
[pyeconomics: Empowering Economic Insight]
pyeconomics
[CI] [PyPI] [Licence] [OpenSSF Scorecard]
Status: 1.0.0b1 is a beta pre-release on PyPI. Install explicitly with
pip install --pre pyeconomics==1.0.0b1(Python 3.12 or later). Plainpip install pyeconomicsstill installs 0.2.6, the stable release. Pre-releases carry no stability promise until 1.0.0.
pyeconomics provides 50 tested, cited economics and finance model
families across 13 domains: foundations, fixed income, derivatives,
international, equity, corporate, accounting, portfolio, performance, risk,
econometrics, macroeconomics and asset pricing. The data platform adds 31
providers, 171 catalog concepts and live bindings with real-time vintages.
Every model is served identically through the Python API, the pyeconomics
command line, the REST API (pyeconomics serve), the MCP server
(pyeconomics mcp) and tabular or reproducibility-bundle exports.
Typed inputs declare units and bounds; every result carries
a reproducible provenance manifest. Rates and percentages are decimals:
0.05 means 5%.
Use the 1.0 documentation preview
for formulas, assumptions and examples, and the
beta release notes
for the shipped surfaces and known limitations. See the
CLI guide,
REST API guide,
MCP server guide,
exports guide,
AI narrative guide,
data guide and
keys guide to get
started. Install optional econometrics, plotting, REST API and MCP support
with pip install --pre "pyeconomics[econometrics,plot,server,mcp]==1.0.0b1",
or run the MCP server directly with
uvx --from "pyeconomics[mcp]==1.0.0b1" pyeconomics mcp.
This beta replaces the 0.2.x API and adds the command line, exports and reproducibility bundles, REST API, MCP server and optional AI narrative on top of the model engine and data platform. The web app arrives in Phase 5; the project roadmap and architecture decisions record that plan. Keep legacy workloads in a separate environment.
pyeconomics 0.2.x
0.2.6 is the current stable release of the 0.2.x line: four monetary-policy rules over FRED data.
- It is MIT-licensed. Its source lives on the
legacy/0.2.xbranch, and its documentation at https://pyeconomics.readthedocs.io/. - It receives security fixes only, and reaches end of life when 1.0.0 is
released. Pins such as
pyeconomics<1keep working. - 0.2.0 to 0.2.5 log the FRED API key at DEBUG level. Upgrade to 0.2.6 and rotate any key those versions used: see advisory GHSA-j6rp-vwwv-jrr8.
Not to be confused with
This project is not davidrpugh/pyeconomics
(computational-economics course code from 2013–14) or
pyecon.org (a site teaching Python for economics). The
three share only the name.
Contributing and security
- CONTRIBUTING: setup, DCO sign-off, commit conventions and the model definition of done.
- SECURITY: report a vulnerability privately, never in a public issue.
- Code of Conduct.
- Changelog.
Licence
From 1.0, pyeconomics is licensed under the Apache License 2.0; see also NOTICE. Releases up to and including 0.2.x remain MIT-licensed.
Notices
As is; not investment advice. pyeconomics is for educational and informational use only, and is not registered with any regulator.
CFA® and Chartered Financial Analyst® are trademarks owned by CFA Institute. pyeconomics is not affiliated with, endorsed by, or a Prep Provider of CFA Institute.
Source: README.md at commit 206c2fa
Tools
0Version history
1- v1.0.0b1LatestOct 29, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts