DataCharter

Query all your data locally. Hand agents exactly the columns you choose.

A local SQL workspace over files and databases, federated by DuckDB and governed by charter.yaml. Agents get read-only, PII-masked access to what the contract grants. Apache-2.0. No paid edition.

datacharter.dev · Docs · Desktop · GovBench · Deploy

Two ways in. Same kernel.

Laptop

Drop a file. Query it. Chart it. An agent sees ••• where PII lives.

uvx datacharter serve          # demo workspace, http://127.0.0.1:8321
# or: datacharter init --from && datacharter serve
# or: datacharter init --template life && datacharter serve --local

No terminal: desktop app (beta). macOS (Apple Silicon) or Windows. Unsigned until Apple secrets exist.

brew install datacharter/tap/datacharter   # macOS
pip install datacharter                    # Python 3.11+

The workspace is a directory: charter.yaml, queries/, guides/. Commit it. Secrets stay out. Optional agent: SpaceXAI, Claude Code, Ollama (--local), or any OpenAI-compatible endpoint.

Company

The same binary, on a shared MCP endpoint. Identities live in git, not on our servers. No rows leave your infrastructure.

datacharter mcp --http --host 0.0.0.0   # OAuth env required off loopback
helm install datacharter ./chart \
  --set oauth.issuer=... --set oauth.audience=... --set oauth.jwksUri=...
datacharter govbench --json             # cite corpus govbench-v1

MCP Streamable HTTP (POST /mcp) with optional OAuth 2.1
principals: and grants: in charter.yaml (default-deny on HTTP)
Helm chart and OCI image
Hash-chained audit plus SIEM JSON/OTLP
GovBench: frozen 28-attack corpus, grade A-F

Wrap someone else's MCP server: datacharter mcp --guard "npx -y some-mcp-server".

What the contract enforces

PII default-deny, row filters, plain-English policies (aggregates only), canaries, a flight recorder, datacharter redteam, access diff on PRs. CLI reference: docs/cli.md. Security: docs/security.md.

Status: pre-release. V1 in development.

Privacy

Runs on your machine or in your cluster. No telemetry. No DataCharter-operated data plane. Privacy Policy.

License

Apache-2.0

Metadata

Release files for datacharter 0.44.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for datacharter 0.44.0
File	Size	Uploaded
datacharter-0.44.0.tar.gz	8.7 MB	Sep 15, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for datacharter 0.44.0
File	Interpreter	ABI	Platform	Reset
datacharter-0.44.0-py3-none-any.whl 4.1 MB Sep 15, 2026	Python 3	none	any	Details

Total release size: 12.8 MB

Release files / datacharter-0.44.0.tar.gz

Download URL	datacharter-0.44.0.tar.gz
Size	8.7 MB
Tags	Source
SHA-256 checksum How to use checksums	`00deaf124177e5d293612f3e7ce21612854fba266ea2aa0bd1abfb49edd09607`
BLAKE2b-256 checksum How to use checksums	`8880967649485d43bd09ebe64ebc3e4fcf0cdb6cb34eff3d7db782d1d3f6ccbf`
Upload date	Sep 15, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/datacharter/datacharter
Publishing commit: github.com/datacharter/datacharter/tree/a7cb14e538d86eb16ad639a9d0799e9206cabfcf

Workflow

Publishing configuration: github.com/datacharter/datacharter/blob/a7cb14e538d86eb16ad639a9d0799e9206cabfcf/.github/workflows/release.yml
Publishing logs: github.com/datacharter/datacharter/actions/runs/35035757200/attempts/1

Artifact

Subject: datacharter-0.44.0.tar.gz
SHA-256 checksum: 00deaf124177e5d293612f3e7ce21612854fba266ea2aa0bd1abfb49edd09607 Verifying attestations

Release files / datacharter-0.44.0-py3-none-any.whl

Download URL	datacharter-0.44.0-py3-none-any.whl
Size	4.1 MB
Tags	Python 3
SHA-256 checksum How to use checksums	`5a95de93152807d12198a883361817ac2a508ce8924a01c937bb4548efd012c9`
BLAKE2b-256 checksum How to use checksums	`570f10d35fb586710f5e0c26c4fb30dce5087e0d6573a153112f670cdaeb256a`
Upload date	Sep 15, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/datacharter/datacharter
Publishing commit: github.com/datacharter/datacharter/tree/a7cb14e538d86eb16ad639a9d0799e9206cabfcf

Workflow

Publishing configuration: github.com/datacharter/datacharter/blob/a7cb14e538d86eb16ad639a9d0799e9206cabfcf/.github/workflows/release.yml
Publishing logs: github.com/datacharter/datacharter/actions/runs/35035757200/attempts/1

Artifact

Subject: datacharter-0.44.0-py3-none-any.whl
SHA-256 checksum: 5a95de93152807d12198a883361817ac2a508ce8924a01c937bb4548efd012c9 Verifying attestations