Connect Antigravity to Oracle through SQLcl’s Model Context Protocol (MCP) server, not through a direct database connection. SQLcl exposes tools to Antigravity and connects through a saved SQLcl profile; the database account and its grants determine what those tools can do. Begin with a read-only account and a bounded validation query. Add Oracle AI Agent Memory only if you need scoped context to persist across sessions.
How the workflow fits together
The workflow has two complementary loops. For an immediate request, Antigravity discovers and calls tools exposed by SQLcl MCP; SQLcl runs the requested operation against its saved Oracle connection and returns results to the agent. For context that must persist, application code can store histories, tool logs, memory records, chunks, and embeddings in Oracle AI Database, then retrieve selected context for later steps.
These loops do different jobs: SQLcl MCP provides live tool access, while Oracle AI Agent Memory provides APIs for durable memories, scoped retrieval, and context assembly. Oracle’s reference architecture also identifies LangChain as an optional application-side orchestration layer.
- Antigravity: the developer-facing MCP client and agent interface.
- SQLcl MCP: the tool boundary through which Antigravity can use SQLcl connections and operations.
- Oracle AI Database: the durable store for data and, when needed, retrieval evidence, vectors, metadata, and traces.
- Oracle AI Agent Memory: application APIs for users, agents, threads, durable memories, retrieval, and context assembly.
- LangChain: an optional wrapper for application-side retriever, document, or chain orchestration.
Oracle’s September 18, 2026 guide describes this architecture and a companion notebook. The notebook is a build-and-validation harness, not another runtime layer: it checks SQLcl and Java discovery, previews sanitized MCP configuration, validates a saved connection alias, creates memory tables, inserts simulated traces, exercises lexical, vector, and hybrid retrieval, initializes the memory package, and captures a validation snapshot.
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What you need before configuring Antigravity
Oracle’s guide specifies SQLcl 25.2.0 or later and JRE 17 or 21 for its example. It also requires Antigravity MCP configuration, a saved SQLcl profile with password persistence, and a database user limited to the privileges the workflow requires. Configuration keys and tool names can vary by release, so check the instructions for the versions installed in your environment.
- Use an approved development, replica, or otherwise sanitized database for initial work.
- Prepare a minimum-permission account; use read-only access for the first validation.
- Install SQLcl and the required Java runtime, and confirm SQLcl is discoverable with
sql -V. - Decide how the local saved-password store will be protected under your organization’s secrets policy.
- Use separate credentials and policies for development, test, and production.
Build the local SQLcl MCP connection
1. Save and test a SQLcl connection
Create a named connection with the approved account, then test the alias directly in SQLcl before involving Antigravity. Oracle’s guide gives this pattern:
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conn -save antigravity_mcp -savepwd <ORACLE_USER>/<ORACLE_PASSWORD>@<ORACLE_DSN>
Replace the angle-bracketed values with your approved database username, password, and connection descriptor. The saved alias is the route the agent uses to reach the database; do not ask the agent to invent or supply connection credentials at runtime. Treat the saved-password store as a secret, and avoid exposing credentials in configuration previews, logs, or prompts.
2. Add SQLcl as an Antigravity MCP server
In Antigravity’s MCP configuration, add a server entry that launches the absolute path to the SQLcl executable with the -mcp argument. Oracle’s example uses mcp_config.json; use the configuration location and schema required by the Antigravity release you have installed. Keep secrets out of this file where possible, and preview or share only sanitized configuration.
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3. Validate with one bounded, read-only request
- In SQLcl, connect using the saved alias and confirm it reaches the intended database.
- Reload Antigravity’s MCP configuration and confirm the SQLcl tools are visible to the client.
- Ask Antigravity for one read-only query with bounded results, such as a small sample from an approved table or a simple metadata check.
- Verify that the result is from the expected connection and that it contains no data beyond what the account should be able to read.
If the tools do not appear, recheck the absolute SQLcl executable path, the -mcp argument, and the installed release’s MCP configuration format. If the connection fails in SQLcl itself, resolve the saved alias or database connectivity first; Antigravity cannot correct a broken SQLcl connection.
Keep the tool boundary secure
MCP makes tool access explicit, but it does not authorize or secure database actions by itself. The saved connection, database user, grants and roles, network controls, and database policies determine what SQLcl tools can read or change. A tool call can only be as constrained as the identity and database path behind it.
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- Start read-only and grant additional privileges only for a defined workflow need.
- Review SQLcl and database activity before expanding access; require explicit approvals for risky actions.
- Log the relevant tool, identity, timestamp, status, and sanitized input/output context.
- Keep production credentials and policies separate from development and test access.
Oracle’s SQLcl documentation is available in the SQLcl 26.1 documentation. Confirm version-specific command and configuration details against the release you use.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Decide whether durable memory belongs in the workflow
Add Oracle AI Agent Memory when later steps need thread history, persistent user or agent memories, scoped recall, or assembled context. In Oracle’s example, Python APIs manage threads, durable memories, retrieval, and context assembly, while Oracle AI Database provides durable storage. This layer is separate from SQLcl’s live database tools: it does not need to be added merely to let Antigravity call SQLcl MCP.
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The example notebook’s default path uses a local deterministic embedder, so a provider-backed embedding or LLM key is not required for that path. A key is needed if you modify the notebook to call provider-backed embedding or LLM services.
When LangChain is useful
LangChain is optional. Consider it when an application needs reusable retriever, document, or chain orchestration; it is not a prerequisite for Antigravity to call SQLcl MCP tools.
Choose a deployment model
Local SQLcl MCP suits hands-on development, prototyping, and individual productivity. For centrally administered or team deployments, Oracle describes managed OCI Database Tools MCP and an ORDS-based MCP endpoint. The placement, administration, and identity model differ:
| Option | Deployment and access model | When it may fit |
|---|---|---|
| SQLcl MCP | Local SQLcl process with saved SQLcl connections. | Local development, prototyping, and individual developer workflows. |
| OCI Database Tools MCP | Managed, serverless OCI service with OCI IAM integration. | Centrally managed access to Oracle cloud databases. |
| ORDS MCP | ORDS Standalone with an HTTPS streaming /mcp endpoint, database connection pools, and OAuth-related identity integration as described by Oracle. |
Teams using existing ORDS deployment patterns and their chosen identity provider. |
Oracle’s MCP overview describes these models. Confirm current feature availability, identity options, and deployment requirements for your region and environment before choosing one.
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Oracle AI Developer Advocate Srinidhi Sathyamurthy writes: “Production success depends less on clever prompting and more on boundaries, privileges, logging, scoped retrieval, and repeatable runbooks.” The practical implication is to treat the local connection as a controlled integration, not as a grant of broad database access. Document the approved alias, account privileges, tool scope, logging expectations, and recovery path before enabling additional operations or moving to production.
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