Palantir MCP is an implementation of the Model Context Protocol ↗. Palantir MCP enables AI IDEs and AI agents to autonomously design, build, edit, and review end-to-end applications within the Palantir platform, covering everything from data integration to ontology configuration and application development. In addition, you can use Palantir MCP to allow external AI systems to query documentation, metadata, and data, as well as perform high-level tasks on the platform. Developers can use Palantir MCP to automate auxiliary tasks while they stay focused on the system they are building.
To get started with the Palantir MCP, first follow the Palantir MCP installation documentation.
Next, try one of the prompts below.
If you need coding help, the Palantir MCP can help by searching the Palantir documentation or getting context about your current repository.
In a TypeScript OSDK repository:
Copied!1What ontology objects do I have in my OSDK?
In a Python transforms repository:
Copied!1Can you rewrite this Python transform to use lightweight?
If you are working in a Python transforms repository, it is often necessary to understand the contents of a dataset. You can prompt the model to analyze datasets for you by providing a dataset RID.
Replace the in the prompt below with a dataset RID, or reference an existing transform.
Copied!1Can you please find an appropriate primary key in this dataset: <RID>?
If you are working on a TypeScript OSDK application, it is common to reference data that may not be in the Ontology yet. Instead of breaking focus on your current task, you can ask the MCP to create mock data for you and continue working on your application.
Copied!1 2 3 4 5I'm working on this OSDK application and need to reference some user data that I don't have in my OSDK yet. Can you please create a new mock user dataset, create a new User Ontology object, and then create a pull request for me? The user dataset should have the columns: user_id, name, email
Palantir is continually developing more tools, prompts, and resources to improve Palantir MCP. Currently, Palantir MCP provides the following tools:
| Tool name | Description |
|---|---|
| create_and_write_to_foundry_dataset | Creates a dataset in Foundry with data provided from a CSV file, useful for uploading local data or creating mock data. |
| create_foundry_branch | Creates a new Foundry branch with a specified display name and description. |
| create_or_update_foundry_object_type | Creates or updates object types in the ontology on a provided branch. |
| delete_foundry_object_type | Deletes an object type from the ontology on a provided branch. |
| generate_new_ontology_sdk_version | Adds ontology entities modified by a given foundry proposal to the ontology SDK and generates a new version of that SDK. |
| get_foundry_dataset_schema | Returns the definition of a Palantir dataset for a given dataset RID or dataset path, including schema information. |
| get_foundry_ontology_rid | Fetches the Ontology RID for a given Foundry OSDK application or local repository. |
| get_ontology_sdk_context | Fetches curated documentation about the Ontology SDK for the user's OSDK repository. |
| get_or_create_foundry_proposal | Creates a new Foundry proposal, which is the final step of a Foundry branch. |
| get_python_transforms_documentation | Fetches curated documentation about Python transforms and the transforms.api SDK. |
| list_resources_in_foundry_folder | Returns the first 20 resources available in a given folder or project RID, with pagination support. |
| run_sql_query_on_foundry_dataset | Returns the result of running a SQL query on a Palantir dataset on an optional branch. |
| search_foundry_documentation | Searches Palantir Foundry platform documentation indices for relevant context snippets for a given query. |
| view_foundry_branch | Allows viewing an existing Foundry branch, including branched resources and ontology modifications. |
| view_foundry_object_type | Allows viewing an existing object type in the ontology. |