agami-core — governed semantic model, the shared MCP TOOLS harness, and the unified local query executor.
Project description
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:
- Deploy the Docker bundle → deploy/README.md
- Manual install + full env-var reference → docs/self-hosting.md
- Use agami from Claude Desktop (stdio) → docs/mcp-server.md
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.
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