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  • Antigravity
    {
      "mcpServers": {
        "edisyl-docs": {
          "serverUrl": "https://docs.edisyl.com/mcp"
        }
      }
    }
  • Claude CodeCLI
    claude mcp add edisyl-docs https://docs.edisyl.com/mcp --transport http --scope user
  • CodexCLI
    codex mcp add --url https://docs.edisyl.com/mcp edisyl-docs
  • Cursor
    {
      "mcpServers": {
        "edisyl-docs": {
          "type": "http",
          "url": "https://docs.edisyl.com/mcp"
        }
      }
    }
  • Gemini CLI
    gemini mcp add --transport http edisyl-docs https://docs.edisyl.com/mcp
  • Goose
    {
      "extensions": {
        "edisyl-docs": {
          "enabled": true,
          "name": "edisyl-docs",
          "type": "streamable_http",
          "uri": "https://docs.edisyl.com/mcp",
          "envs": {},
          "env_keys": [],
          "headers": {},
          "description": "",
          "timeout": 300,
          "bundled": null,
          "available_tools": []
        }
      }
    }
  • JetBrains AI Assistant
    {
      "mcpServers": {
        "edisyl-docs": {
          "type": "http",
          "url": "https://docs.edisyl.com/mcp"
        }
      }
    }

    Paste into Settings → Tools → AI Assistant → Model Context Protocol → Add → As JSON. Direct file writing isn’t supported — JetBrains stores this per-version as XML.

  • Junie (JetBrains)
    {
      "mcpServers": {
        "edisyl-docs": {
          "url": "https://docs.edisyl.com/mcp"
        }
      }
    }
  • OpenCode
    {
      "mcp": {
        "edisyl-docs": {
          "type": "remote",
          "url": "https://docs.edisyl.com/mcp"
        }
      }
    }
  • VS CodeCLI
    code --add-mcp '{"name":"edisyl-docs","type":"http","url":"https://docs.edisyl.com/mcp"}'
  • Windsurf
    {
      "mcpServers": {
        "edisyl-docs": {
          "serverUrl": "https://docs.edisyl.com/mcp"
        }
      }
    }

    Supports both stdio and native HTTP connections.

Task

Use a task for work that needs the pack’s agents to do something, not answer a question or record a fact. Examples are researching a topic and adding it to the pack, fixing what the pack covers, or modeling new data.

task starts the pack’s task agent with your objective. It returns a task Action immediately.

Input Type Required Meaning
packId string Yes The pack’s id or slug, from list_packs.
objective string Yes The objective for the pack’s agent, in natural language.
mustWrite boolean No Fail the task, instead of succeeding, if nothing it writes reaches the pack.
mode standard or fast No Stored as given. It does not change how the task runs. Both modes use the same executor.
idempotencyKey string No A key you choose for this attempt, up to 200 characters. If you retry with the same key, you get back the Action the first attempt created.

Returns the Action. Call action_get with its actionId and waitSeconds until the status is final. A succeeded task returns output.summary, output.artifactIds, and output.knowledgeWrites. output.knowledgeWrites lists what the task wrote to the pack, as the pack recorded it. While the task runs, phase shows the tool its agent called last.

Permission: task needs steer access on the pack.

“Research how the validator docs have changed this quarter and write a dated summary into the pack.”

A task runs one executor agent over the pack. The agent uses ask to answer the questions the objective raises, one precise question at a time. It gives large or independent pieces of work to subtasks. It can also research the open web and add its findings to the pack. It can run ask and teach itself, as child Actions.

A task can produce a report, an artifact, an external action (when explicitly authorized), or a proposed change that needs review. It adds new understanding to the pack only when the objective explicitly asks it to teach. A task never changes the pack’s understanding without being asked:

"Research competitor pricing and report back." → a result only
"Research competitor pricing and teach the findings." → a result, and a teach on the same pack

In the CLI, add --cron or --at to make any task a schedule. In MCP, use the schedule_* tools. See Scheduling recurring work and schedule.

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