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Adds a governed trust layer between AI agents and databases with auditable query receipts.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "agami-core" yet — see the docs or source repo.
Route this database-facing AI request through agami-core: join the users and orders tables and calculate monthly GMV. Require sign-off for joins and metric changes, and generate an auditable receipt for the final query.
Returns a governed query result showing join and metric approvals plus an auditable receipt.
Have the AI agent query the database through agami-core and record an auditable receipt for every query for later review.
Produces query results along with audit record information for each request.
Use agami-core to run an AI-generated analytics query; if it introduces a new metric definition or changes an existing metric, require sign-off first.
Blocks metric-related queries until approval is granted, then returns results with a receipt.
Developers or data teams can place it between AI agents and databases to add a governed trust layer. Queries involving joins and metrics require sign-off before execution and leave auditable records.
When teams need to review what database queries an AI agent issued, this MCP server generates an auditable receipt for every query. It fits environments that need strong traceability for data access.
If an AI agent may freely create table joins or redefine business metrics, this tool can require sign-off for those actions. That adds a governance checkpoint before execution.
It is a governed MCP server that sits between AI agents and databases. It requires sign-off for joins and metrics and produces an auditable receipt for every query.
It is suitable when AI agents need database access but teams also want stronger governance and auditing. It is especially useful for controlling joins, metric definitions, and query traceability.
The provided information only says it is an MCP server between AI agents and databases. For installation steps, runtime, and prerequisites, see the source repository.
Create tamper-proof audit logs, integrity checks, and compliance reports for AI agents.
Provide tamper-evident receipts, trust scoring, and capability tokens for AI agents.
Audit MCP servers and AI packages for security and supply chain risks.
Audit AI agent permissions by scanning credential, injection, and reach risks.
Manage agent credentials, spending, approvals, and audit trails safely.
Verify, score, route, compare, and delegate AI agent decisions.