mcpField
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DataCharter

DataCharter

Local
github.com/datacharterData & Analytics15Updated 6w ago
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About DataCharter

DataCharter is a local-first SQL workspace for data teams and AI agents. Its YAML contract controls read-only, PII-masked access to files and databases, with local and shared MCP deployment options.

Key features

  1. 01Federated SQL over files and databases
  2. 02Contract-based column and row access
  3. 03PII masking and default-deny policies
  4. 04Charts and query workspace
  5. 05Audit logs and access-diff checks

Use cases

  1. 01Let agents query approved data fields
  2. 02Explore local files and databases
  3. 03Restrict access to sensitive or row-level data

MCP support

Exposes contract-governed data access through an MCP endpoint using Streamable HTTP, with optional OAuth 2.1. It can also guard another MCP server.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "datacharter-datacharter": {
      "command": "uvx",
      "args": [
        "datacharter"
      ]
    }
  }
}
Run commanduvx datacharter

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypidatacharter0.44.0

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

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.

PyPI Python License: Apache-2.0

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

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

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