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Assiststudio Runner logo
Health: ActiveRecent health check succeeded.Last checked 9/7/2026, 7:58:33 PM

Assiststudio Runner

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
View Repository1 GitHub StarsTotal stargazers on GitHub for the source repository (1 stars).Visit Website

Windows-only headless LLM task automation engine with scheduling via Windows Task Scheduler.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Remote HTTP
Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "assiststudio-runner": {
      "url": "https://img.shields.io/nuget/v/FieldCure.AssistStudio.Runner)](https://www.nuget.org/packages/FieldCure.AssistStudio.Runner"
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸ’» More in Developer Tools

Documentation Overview

AssistStudio Runner

NuGet License: MIT

A Windows-only headless LLM task automation engine that executes natural language tasks on schedule and delivers results through configured channels. Built as a Model Context Protocol (MCP) server with the official MCP C# SDK.

Features

  • Dual-mode operation β€” MCP server (serve) for task management, headless CLI (exec) for scheduled execution
  • 7 MCP tools β€” create_task, update_task, delete_task, list_tasks, run_task, get_task_history, get_execution_status
  • Windows Task Scheduler integration β€” cron expressions automatically mapped to schtasks entries
  • Shared AgentLoop β€” LLM execution powered by Ai.Execution (same loop used by SubAgentExecutor)
  • Multi-provider LLM support β€” Claude, OpenAI, Gemini, Ollama, Groq via Ai.Providers
  • MCP server orchestration β€” tasks can bootstrap any MCP servers (Outbox, RAG, Filesystem, custom)
  • Flexible tool control β€” AllowedTools null = all tools permitted; explicit list for fine-grained control; empty list = safe tools only
  • Secure credentials β€” API keys in Windows Credential Manager (DPAPI), shared with AssistStudio
  • Execution logging β€” DB summary + detailed JSON logs with full conversation history
  • One-time scheduling β€” schedule_once with ISO 8601 datetime for single-execution tasks (β€œin 5 minutes”, β€œtomorrow at 9am”)
  • Result delivery β€” send results via Outbox channels (Slack, Telegram, Email, KakaoTalk, Discord)

Installation

dotnet tool (recommended)

bash
dotnet tool install -g FieldCure.AssistStudio.Runner

After installation, the assiststudio-runner command is available globally. The published package is Windows-only because scheduling is implemented via Windows Task Scheduler and credentials are stored in Windows Credential Manager.

From source

bash
git clone https://github.com/fieldcure/fieldcure-assiststudio-runner.git
cd fieldcure-assiststudio-runner
dotnet build

Requirements

  • .NET 8.0 Runtime or later
  • Windows (required for Task Scheduler and Credential Manager)

Configuration

Auto-configuration (recommended)

When launched in serve mode with no runner.json, Runner automatically scans Windows Credential Manager for known provider API keys and generates the config file. If you use AssistStudio, API keys are already stored β€” no manual setup needed.

Manual Setup

bash
# Create runner.json config template
assiststudio-runner config init

# Set API key for a provider model
assiststudio-runner config set-credential "Claude" sk-ant-api03-...

# Verify (displays masked value)
assiststudio-runner config get-credential "Claude"

The config file is created at %LOCALAPPDATA%/FieldCure/AssistStudio/Runner/runner.json:

config.json
{
  "defaultModelName": "Claude",
  "models": {
    "Claude": {
      "providerType": "Claude",
      "modelId": "claude-sonnet-4-20250514"
    }
  },
  "fallbackChannel": "runner-alerts",
  "logRetentionDays": 30
}

Claude Desktop

Add to claude_desktop_config.json:

config.json
{
  "mcpServers": {
    "runner": {
      "command": "assiststudio-runner",
      "args": ["serve"]
    }
  }
}

VS Code (Copilot)

Add to .vscode/mcp.json:

config.json
{
  "servers": {
    "runner": {
      "command": "assiststudio-runner",
      "args": ["serve"]
    }
  }
}

From source (without dotnet tool)

config.json
{
  "mcpServers": {
    "runner": {
      "command": "dotnet",
      "args": [
        "run",
        "--project", "C:\\path\\to\\fieldcure-assiststudio-runner\\src\\FieldCure.AssistStudio.Runner",
        "--", "serve"
      ]
    }
  }
}

Tools

ToolDescriptionConfirmation
create_taskCreate a task with prompt, schedule, and MCP server configRequired
update_taskModify task fields β€” partial update, only changed fieldsRequired
delete_taskDelete a task, its executions, and log filesRequired
list_tasksList tasks with filtering and last execution statusβ€”
run_taskStart execution (async default, optional 60s wait)Required
get_task_historyQuery execution history with status filteringβ€”
get_execution_statusCheck real-time status of an executionβ€”

Usage

Conversation Example

Code
User: "Summarize competitor news every morning at 9 AM and send it to Slack"
  LLM β†’ create_task (schedule: "0 9 * * 1-5", mcp_servers: [outbox, rag])

User: "Run a test"
  LLM β†’ run_task (wait: true) β†’ reports result

User: "Exclude weekends"
  LLM β†’ update_task (schedule: "0 9 * * 1-5")

User: "What were yesterday's results?"
  LLM β†’ get_task_history (limit: 1)

Execution Modes

ModeCommandPurpose
Serveassiststudio-runner serveMCP server (stdio) for task management
Execassiststudio-runner exec <task-id>Headless execution (called by schtasks)
Configassiststudio-runner config initCreate config template
assiststudio-runner config set-credential <key> <value>Store API key or env var
assiststudio-runner config get-credential <key>Retrieve credential (masked)

Exit Codes (exec mode)

CodeMeaning
0Succeeded
1Failed
2Timed out
3Task not found
4Already running

Scheduling

Cron expressions are automatically mapped to Windows Task Scheduler entries:

ScheduleParameterschtasks
Once at specific timeschedule_once: "2026-04-07T15:30:00+09:00"/SC ONCE /SD 2026/04/07 /ST 15:30
Every 30 minutesschedule: "*/30 * * * *"/SC MINUTE /MO 30
Every 2 hoursschedule: "0 */2 * * *"/SC HOURLY /MO 2
Daily at 9:00 AMschedule: "0 9 * * *"/SC DAILY /ST 09:00
Weekdays at 9:00 AMschedule: "0 9 * * 1-5"/SC WEEKLY /D MON,TUE,WED,THU,FRI /ST 09:00
Monthly on the 1stschedule: "0 9 1 * *"/SC MONTHLY /D 1 /ST 09:00

Scheduled tasks are created with schtasks /IT, so they run in the interactive user context and require the user to be logged in at trigger time.

The schtasks command line uses dnx (NuGet's npx-equivalent, .NET 10+) to fetch and run the worker β€” dnx FieldCure.AssistStudio.Runner@<major>.* --yes exec <id>. Stateless MCP servers consumed by the worker (Essentials, Outbox) are spawned the same way, pinned at their current major range. Set RunnerConfig.ToolPath to override with a concrete executable when an offline-from-NuGet workflow is required.

Data Storage

DataLocation
Configuration%LOCALAPPDATA%/FieldCure/AssistStudio/Runner/runner.json
Task database%LOCALAPPDATA%/FieldCure/AssistStudio/Runner/runner.db (SQLite, WAL)
Execution logs%LOCALAPPDATA%/FieldCure/AssistStudio/Runner/logs/{id}.json
API keysWindows Credential Manager (FieldCure.AssistStudio)

Project Structure

Code
src/FieldCure.AssistStudio.Runner/
β”œβ”€β”€ Program.cs                    # Dual-mode entry point (serve/exec/config)
β”œβ”€β”€ Models/                       # RunnerTask, TaskExecution, RunnerConfig, ExecutionLog
β”œβ”€β”€ Storage/TaskStore.cs          # SQLite storage with WAL mode
β”œβ”€β”€ Credentials/                  # ICredentialService + Windows PasswordVault
β”œβ”€β”€ Scheduling/                   # CronToSchtasks parser, SchedulerService (schtasks)
β”œβ”€β”€ Execution/                    # TaskExecutor (AgentLoop-based), McpServerPool
β”œβ”€β”€ Tools/                        # 7 MCP tools for serve mode
└── Configuration/ConfigRunner.cs # CLI config subcommands

Development

bash
# Build
dotnet build

# Test
dotnet test

# Pack
dotnet pack -c Release

Designed for AssistStudio

Runner is purpose-built for the AssistStudio ecosystem. Tasks are typically created through natural language conversations in AssistStudio, which handles workflow design, MCP server selection, and tool permissions automatically.

While Runner can be used standalone with Claude Desktop or VS Code (via serve mode), you'll need to construct task parameters (prompt, MCP servers, allowed tools) manually. For the full experience, use AssistStudio.

See Also

Part of the AssistStudio ecosystem.

License

MIT

Read the full README β†’View source on GitHub β†’

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Reviews

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Frequently Asked Questions about Assiststudio Runner

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "assiststudio-runner": { "command": "npx", "args": ["-y", "assiststudio-runner"] } }

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Technical Specs & Signals

CategoryπŸ’»Developer Tools
More technical detailsExpand β–Ύ
TransportSSE (Remote)
RuntimeNode.js
Last updatedSep 7, 2026
Views0
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars1
GitHub Star CountTotal stargazers on GitHub representing community popularity (1 stars).
36Quality signal: Fair Β· 36/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools16/30
Adoption & activity1/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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