How Palantir Unifies Claude, OpenAI, and Google Agents on a Shared Ontology Layer

01 Palantir Unifies the Enterprise Agent Access Layer

On July 9, 2026 Palantir released three Agent SDK templates for Claude, OpenAI, and Google. Instead of merging the three frameworks, Palantir lets them share Ontology resource scopes, authentication methods, MCP interfaces, and publishing workflows. The real focus is not supporting three frameworks but providing a common enterprise runtime base consisting of business objects, permissions, state, and action boundaries.

02 Why Ontology Becomes the Stable Layer for Enterprise Agents

Large language models can understand natural language but do not inherently understand how a business operates. A database row may represent a delinquent order, a risky supplier, or a device awaiting repair. Ontology maps these business nouns, their relationships, current states, allowable actions, and the identities that can perform them. Actions encode governed business changes, while Functions encapsulate reusable logic.

When an Agent works through Ontology, it interacts with semantically enriched entities rather than raw tables. For example, an Agent can read an order and its linked inventory, compute impact via a query function, and modify the order status only through a pre‑defined, permission‑guarded Action.

This goes beyond traditional Retrieval‑Augmented Generation (RAG) which only answers “what can be retrieved”. Ontology adds answers to “what does the data represent”, “how are objects related”, and “which actions are permissible”, which are critical for production‑grade Agents.

03 OSDK, Ontology MCP, and Palantir MCP Solve Different Problems

Palantir provides three components:

OSDK – a code‑level SDK where developers select object types, Action types, and query functions, generating a typed client that reads or writes Ontology data.

Ontology MCP – a model‑level service that exposes the same object types, Actions, and queries as MCP tools discoverable by running models. Write operations are performed via defined Actions, not direct database writes.

Palantir MCP – a platform‑level service for AI IDEs and Agent development, offering repository inspection, data transformation, Ontology schema management, and application creation. It can modify Ontology structure but cannot write business data directly; that responsibility belongs to Ontology MCP.

Consequently, a single Agent chain may involve two kinds of activity: a runtime business Agent changes order status via Ontology MCP, while a development Agent modifies code or Ontology schema via Palantir MCP.

04 Permissions and Action Boundaries Are Deeply Embedded

The most hazardous part of integrating Agents is not model hallucination but unauthorized data reads or unintended actions. Scoped Permissions, provided out‑of‑the‑box, supply the necessary credentials for OSDK, Ontology MCP, and Palantir MCP without requiring developers to embed client IDs or secrets in code.

However, credentials are scoped: an Agent can only access resources allowed by its Ontology binding and Application Restrictions. Thus, permission boundaries move from prompt engineering to Ontology resources, application limits, Action permissions, and submission conditions.

05 Published Agents Behave Like Asynchronous Business Functions

Agents are not real‑time chat products. Each Agent must bind to an Ontology and receive an API name before publishing. After publishing, Foundry registers the Agent as an asynchronous function. Execution is typically triggered by Automate, Workshop, OSDK, or Ontology Action when an Ontology object changes.

Example: a claims‑dispute Agent is triggered after a claim is rejected, reads the claim details, generates an explanation and remediation suggestions, and writes the result back to the claim object, updating its state for downstream processes.

Current limitations include: Agents return Void, cannot directly return query results, do not support streaming or batch calls, and must write outputs back to Ontology objects for downstream consumption.

06 What the Update Actually Changes

Beyond adding three templates, the update signals Palantir’s intent to become the shared enterprise action layer beneath Claude, OpenAI, and Google frameworks. Previously, each new Agent framework required rebuilding data access, tool wrappers, authentication, permission checks, and state‑write logic. Palantir moves these common parts into Ontology, OSDK, and MCP, allowing frameworks to focus on inference loops and tool orchestration.

Migration still requires adapting the Agent loop and tool definitions, but the heavy lifting of object modeling, permission design, and state management is centralized.

07 Production Considerations

Three open issues remain:

The Agent capability is still in Beta, with limited environment availability and evolving feature boundaries.

Framework neutrality does not equal platform neutrality; while any of the three Agent frameworks can be chosen, business objects, Actions, permissions, and publishing workflows remain tightly coupled to Palantir Ontology.

Ontology construction cannot be omitted. Enterprises must still define trustworthy objects, reconcile entity identities across systems, specify permissible Actions, validate parameters, and enforce approvals. Poorly defined objects or overly broad permissions can be amplified by automated Agents.

When Ontology MCP connects to external models or MCP clients, data may flow to outside systems, requiring careful governance, resource exposure controls, and audit mechanisms.

Conclusion

While Agent models and frameworks evolve rapidly, the durable component for enterprise Agents is the Ontology layer that represents business reality—objects, relationships, states, and governed actions.

References: Palantir 2026 announcement, Palantir Agents Overview, Palantir Agent Templates, Palantir Scoped Permissions, Palantir Publish and Call an Agent, Palantir Agents Use Cases, Palantir Ontology MCP Overview, Palantir Ontology MCP Example Workflows, Palantir MCP Overview.