Where you build - Within MCP

You can build inside Within with Advisor or in an external AI client connected through the Within MCP. The right location depends on where the work, tools, and resulting files need to live.

Advisor, the MCP, and your AI client

These components have separate responsibilities.

Component	Responsibility	Boundary
Advisor	Analyze process evidence and create Within-native outputs inside Within	Work remains in the Within product experience
Within MCP	Give an authorized AI client read-only access to Company Brain context and builder methods	It retrieves from Within; it does not write to Within or another system
Your AI client	Reason over the retrieved context and use the client’s tools to create files, code, skills, or actions outside Within	The client’s permissions and approval controls govern those actions

This boundary matters when a build uses several systems. The MCP supplies Within context. If the assistant drafts a document, commits code, or calls another connector, the AI client performs that action through its own tools.

Build inside Within

Use Advisor when the work should stay in Within and the builder wants a guided product experience. Advisor can analyze the Company Brain, help shape a build, and produce Within-native artifacts such as current-state analysis and before-and-after workflow diagrams. This is the usual path for a business user building a skill or exploring a process without working in a code repository. Continue with the non-technical track.

Build from your AI client

Use the MCP when the build needs context or tools available in another client. A business user might combine Company Brain evidence with files available to ChatGPT or Claude. A developer might use Codex, Claude Code, Cursor, or the Gemini CLI to create and test a compound agent in a repository. The client can also combine Within with other connectors. Keep the source boundary explicit in the prompt so the result states which claims came from Within and which came from another system. See Chain with other connectors.

A developer pull pattern

Within exposes two useful levels of process evidence. L3 is the process graph: the process definition, hierarchy, tasks, dependencies, policies, and observation summaries. L4 is the activity timeline behind a specific observation. Start at L3 with the smallest useful process scope, then retrieve L4 evidence only for a claim that needs it.

Locate the process

Use search_processes when you know the topic, or get_process_hierarchy when you need to browse the process tree. If the result is a hierarchy node rather than a leaf process, inspect it with get_hierarchy_node_details before choosing a process.

search_processes({ "query": "shipment exceptions", "top_k": 5 })

get_hierarchy_node_details({
  "node": { "node_resource_key": "<NODE_RESOURCE_KEY>" }
})

Read the current process

Retrieve the process record and request only the scopes needed for the build.

get_process_details({
  "process_resource_key": "<PROCESS_RESOURCE_KEY>",
  "scope": ["tasks", "dependencies", "policies", "history"]
})

Check representative observations

Scan summaries first. Open the underlying activity timeline only for the observations needed to confirm a material claim.

get_process_observations({
  "process_resource_key": "<PROCESS_RESOURCE_KEY>",
  "limit": 10,
  "offset": 0,
  "verbosity": "summary"
})

get_observation_citation({
  "observation_resource_key": "<OBSERVATION_RESOURCE_KEY>",
  "verbosity": "medium",
  "activity_block_index": 3
})

Activity timelines can be large. Use low or medium verbosity and request one activity_block_index returned by the tool at a time. The citation tool can return timelines only for the authenticated user’s own sessions; if it cannot retrieve one, state that limitation rather than treating the observation summary as primary evidence.

Choose the build method

For a bounded task, ask the assistant to load the Agent Builder skill method through get_agent_builder_instructions. The non-technical track includes a complete example. For a compound build, use the Agent Development Kit sequence served through the MCP. The method guides objective setting, evidence review, design, implementation, evaluation, and deployment in the coding harness. Continue with the technical track.

Connect securely

Use OAuth for interactive clients that support it. Use a workspace-scoped API key for headless or automated connections, store it outside the repository, and rotate it if exposed. Both methods preserve the permissions of the Within user and workspace behind the connection. See Authentication and the setup page for your client.

Connecting the Within MCP does not authorize an external action. Configure write access, approvals, and credentials in the AI client or destination system that performs the action.

​Advisor, the MCP, and your AI client

​Build inside Within

​Build from your AI client

​A developer pull pattern

​Choose the build method

​Connect securely

Advisor, the MCP, and your AI client

Build inside Within

Build from your AI client

A developer pull pattern

Choose the build method

Connect securely