AssistStudio Runner
Result delivery channel via Outbox, allowing task execution results to be sent to Discord.
Result delivery channel via Outbox, allowing task execution results to be sent to KakaoTalk.
Multi-provider LLM support using Ollama for task execution, enabling natural language task automation with local models.
Multi-provider LLM support using OpenAI for task execution, enabling natural language task automation.
Result delivery channel via Outbox, allowing task execution results to be sent to Slack.
Result delivery channel via Outbox, allowing task execution results to be sent to Telegram.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@AssistStudio RunnerSchedule a daily backup reminder at 10am"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
AssistStudio Runner
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 — MCP server (
serve) for task management, headless CLI (exec) for scheduled execution7 MCP tools —
create_task,update_task,delete_task,list_tasks,run_task,get_task_history,get_execution_statusWindows Task Scheduler integration — cron expressions automatically mapped to
schtasksentriesShared AgentLoop — LLM execution powered by Ai.Execution (same loop used by SubAgentExecutor)
Multi-provider LLM support — Claude, OpenAI, Gemini, Ollama, Groq via Ai.Providers
MCP server orchestration — tasks can bootstrap any MCP servers (Outbox, RAG, Filesystem, custom)
Flexible tool control —
AllowedToolsnull = all tools permitted; explicit list for fine-grained control; empty list = safe tools onlySecure credentials — API keys in Windows Credential Manager (DPAPI), shared with AssistStudio
Execution logging — DB summary + detailed JSON logs with full conversation history
One-time scheduling —
schedule_oncewith ISO 8601 datetime for single-execution tasks (“in 5 minutes”, “tomorrow at 9am”)Result delivery — send results via Outbox channels (Slack, Telegram, Email, KakaoTalk, Discord)
Related MCP server: K-Personal MCP
Installation
dotnet tool (recommended)
dotnet tool install -g FieldCure.AssistStudio.RunnerAfter 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
git clone https://github.com/fieldcure/fieldcure-assiststudio-runner.git
cd fieldcure-assiststudio-runner
dotnet buildRequirements
.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 — no manual setup needed.
Manual Setup
# 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:
{
"defaultModelName": "Claude",
"models": {
"Claude": {
"providerType": "Claude",
"modelId": "claude-sonnet-4-20250514"
}
},
"fallbackChannel": "runner-alerts",
"logRetentionDays": 30
}Claude Desktop
Add to claude_desktop_config.json:
{
"mcpServers": {
"runner": {
"command": "assiststudio-runner",
"args": ["serve"]
}
}
}VS Code (Copilot)
Add to .vscode/mcp.json:
{
"servers": {
"runner": {
"command": "assiststudio-runner",
"args": ["serve"]
}
}
}From source (without dotnet tool)
{
"mcpServers": {
"runner": {
"command": "dotnet",
"args": [
"run",
"--project", "C:\\path\\to\\fieldcure-assiststudio-runner\\src\\FieldCure.AssistStudio.Runner",
"--", "serve"
]
}
}
}Tools
Tool | Description | Confirmation |
| Create a task with prompt, schedule, and MCP server config | Required |
| Modify task fields — partial update, only changed fields | Required |
| Delete a task, its executions, and log files | Required |
| List tasks with filtering and last execution status | — |
| Start execution (async default, optional 60s wait) | Required |
| Query execution history with status filtering | — |
| Check real-time status of an execution | — |
Usage
Conversation Example
User: "Summarize competitor news every morning at 9 AM and send it to Slack"
LLM → create_task (schedule: "0 9 * * 1-5", mcp_servers: [outbox, rag])
User: "Run a test"
LLM → run_task (wait: true) → reports result
User: "Exclude weekends"
LLM → update_task (schedule: "0 9 * * 1-5")
User: "What were yesterday's results?"
LLM → get_task_history (limit: 1)Execution Modes
Mode | Command | Purpose |
Serve |
| MCP server (stdio) for task management |
Exec |
| Headless execution (called by schtasks) |
Config |
| Create config template |
| Store API key or env var | |
| Retrieve credential (masked) |
Exit Codes (exec mode)
Code | Meaning |
| Succeeded |
| Failed |
| Timed out |
| Task not found |
| Already running |
Scheduling
Cron expressions are automatically mapped to Windows Task Scheduler entries:
Schedule | Parameter | schtasks |
Once at specific time |
|
|
Every 30 minutes |
|
|
Every 2 hours |
|
|
Daily at 9:00 AM |
|
|
Weekdays at 9:00 AM |
|
|
Monthly on the 1st |
|
|
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 — 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
Data | Location |
Configuration |
|
Task database |
|
Execution logs |
|
API keys | Windows Credential Manager ( |
Project Structure
src/FieldCure.AssistStudio.Runner/
├── Program.cs # Dual-mode entry point (serve/exec/config)
├── Models/ # RunnerTask, TaskExecution, RunnerConfig, ExecutionLog
├── Storage/TaskStore.cs # SQLite storage with WAL mode
├── Credentials/ # ICredentialService + Windows PasswordVault
├── Scheduling/ # CronToSchtasks parser, SchedulerService (schtasks)
├── Execution/ # TaskExecutor (AgentLoop-based), McpServerPool
├── Tools/ # 7 MCP tools for serve mode
└── Configuration/ConfigRunner.cs # CLI config subcommandsDevelopment
# Build
dotnet build
# Test
dotnet test
# Pack
dotnet pack -c ReleaseDesigned 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
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/fieldcure/fieldcure-assiststudio-runner'
If you have feedback or need assistance with the MCP directory API, please join our Discord server