MCP turns project actions into tools
The Model Context Protocol (MCP) is a standard for exposing data and actions to compatible AI clients. Instead of pasting a status document into every prompt, you connect a server whose tools describe the operations the assistant can request.
Hillchart’s MCP package works with Hillchart’s authenticated API. That gives a client structured project context and project operations while keeping access tied to your personal token.
Connect Hillchart to Cursor
First, create a personal API token in Hillchart settings. Treat it like a password: copy it into the MCP client configuration through an environment variable or secret mechanism, and never commit it to the repository.
Add the Hillchart MCP server to Cursor’s MCP configuration using the command and environment expected by the package. Restart or refresh MCP servers, then confirm that Hillchart tools appear before asking the assistant to use them.
- Create a dedicated token in Hillchart settings
- Store the token outside source control
- Confirm the server starts and tools are visible
- Revoke the token if it is exposed or no longer used
Start with read-oriented questions
Begin by asking the assistant to list or inspect a project and summarize its scopes. This confirms that the intended account and project are in view before any write operation.
A useful prompt names the project and the desired output: for example, ask for a concise summary that separates uphill uncertainty from downhill execution. Verify the result against the Hillchart interface.
Review changes before they happen
MCP can make workflows faster, but an AI tool can misunderstand a project name or instruction. Review proposed scope creation, movement, and snapshots before approval. Prefer explicit project identifiers when names are similar.
Use the smallest action that achieves the goal. Reading the project does not require a write. Creating a checkpoint does not require changing scope positions. Clear boundaries make automation easier to trust.
Choose MCP, API, or webhooks by workflow
Use MCP for interactive work with an AI assistant. Use the API when your application or script should make a direct authenticated request. Use webhooks when your service should react to supported Hillchart events.
These interfaces complement one another. A webhook can notify your system that a snapshot was created, while an MCP conversation can help a person interpret the project state. Keep credentials scoped to their environment and make webhook handlers safe to retry.