agami-core

The governed trust layer between an AI agent and your database. The importable core behind the agami Claude Code skill and MCP server — the semantic model, the shared MCP TOOLS harness, and the local query executor.

What it does

Point an AI agent at a database and it answers by guessing — at the join, at what "revenue" means, at which rows it's allowed to read. agami-core turns your schema into a governed semantic model where every join is FK-derived or human-approved and every metric is signed off before the runtime trusts it. Every answer then ships a receipt — the exact SQL it ran and the model version it pinned — so a silent join mistake never reaches you as a confident wrong number.

It runs locally: credentials, schema, and query results never leave your machine.

Most people don't pip install this

If you just want to use agami, install the Claude Code plugin — you don't touch this package directly:

/plugin marketplace add AgamiAI/agami-core
/plugin install agami-core@agami

pip install agami-core is for the other two audiences: importing the library into your own code, or self-hosting the MCP server. Full product docs and the plugin walkthrough live in the repository.

Install

pip install agami-core            # executor + stdio harness (pure-stdlib)
pip install 'agami-core[model]'   # + the semantic model (pydantic / sqlglot / pyyaml)
pip install 'agami-core[server]'  # + the networked HTTP MCP server (see below)

From a checkout, swap in the editable path — pip install -e 'packages/agami-core[model]'.

Importing the library

The top-level names — semantic_model, mcp_harness, execute_sql, agami_paths — are a deliberate flat invariant (no parent package, no sys.path juggling), so a consumer's imports resolve unchanged:

from mcp_harness import TOOLS
import semantic_model
import execute_sql

Module entry points:

python -m mcp_harness                        # the stdio MCP server (Claude Desktop)
python -m execute_sql --sql-file query.sql   # the local query executor
python -m semantic_model.cli                 # the semantic-model CLI (driven by the `sm` launcher)
python -m mcp_http                           # the networked HTTP MCP server (see below)

HTTP MCP server ([server]) — early access, in testing

The [server] extra adds a networked MCP transport: the same TOOLS surface as the stdio server, but over HTTP with OAuth and a small admin console. It's the self-host shape of the hosted product — deploy it to your own host and a whole team connects their own Claude to one URL, zero-egress by default (enabling OIDC/SSO adds one outbound call to your identity provider).

🧪 Early access. This team/server layer is usable today but newer than the local single-player path — expect the occasional rough edge, and please report anything broken via a GitHub issue. The local library and stdio server are the stable path.

A minimal local launch (SQLite store, password admin):

PUBLIC_BASE_URL=https://your-host \
AGAMI_SIGNING_SECRET=$(openssl rand -hex 32) \
AGAMI_DB_URL=sqlite:///$PWD/agami.db \
AGAMI_ADMIN_USERNAME=you@example.com AGAMI_ADMIN_PASSWORD=choose-a-strong-one \
python -m mcp_http

The full detail — the auth/access model, OIDC onboarding, the admin console (Activity + Model views), and every environment variable — lives in the docs rather than here:

Links

  • Repository & full docs — github.com/AgamiAI/agami-core
  • Homepage — agami.ai
  • License — fair-code (source-available), the Agami Functional Use License. Self-hosting for your own organization is free; serving people outside it needs a commercial license.

Project links

Data verified by PyPI on Aug 18, 2026
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  • Released:
Newer release available (0.8.6)

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Credits

Author: Agami AI

GitHub Statistics

Data verified by PyPI on Aug 18, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

LicenseRef-Agami-FUL
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Requires

Python >=3.10

Provides Extra

model server

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