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Managed Agents MCP Server

Community

A local-first AI agent runtime with an MCP bridge.

GitHub source repository ↗

★ 634 Stars Category · Dev Tools Very popular Source revision 964763189c25

44FMRS · D

Reliability

8/20

Security and permissions

8/20

Maintenance

7/20

Documentation

11/20

Setup experience

10/20

The supplied sources describe a local agent runtime with MCP tools and a native DeepSeek Harness stdio bridge. No concrete MCP tool identifiers are listed, so the tool list is empty.

Read the FMRS scoring method →

Managed Agents is a local-first AI agent runtime providing persistent sessions, sandboxed tools, memory, credentials, audit trails, replay, and a local Console, with DeepSeek Harness integration over stdio MCP.

Tools

The tool list has not been reviewed yet.

Setup

Set MANAGED_AGENTS_URL=http://127.0.0.1:3000. Install the bundle into a DSH profile with dsh plugin --profile web add managed-agents, then run dsh web. Start managed-agents before using the profile.

Fit and risk

Best for

Developers needing a local or self-hosted agent runtime
Teams requiring persistent sessions, auditability, and replay
Users working with DeepSeek Harness and MCP

Not for

Users seeking a hosted model service
Users seeking a visual workflow builder
Environments without Node.js 22+ or a model-provider API key

Required permissions

Access to the local runtime and its workspace state directory
Depending on configuration, local-process, Docker, Kubernetes, or self-hosted worker permissions
A configured model-provider API key for model execution

Risks and side effects

Misconfigured sandbox backends may broaden tool access to the host or infrastructure
Credentials, files, memory, and audit data are stored in the runtime workspace or configured storage backends
After API-key authentication is enabled, key holders can make authorized runtime requests

Troubleshooting

Verify that Node.js 22+ and npm 10+ are installed
Verify that managed-agents is running and MANAGED_AGENTS_URL is correct
Check the model provider and API key under Settings > Models
If using Docker, verify Docker availability; if using Kubernetes, verify kubectl and cluster permissions
Check the DSH profile installation and logs for the stdio MCP process

Use cases

Manage and run AI agent sessions

Execute tools through sandbox backends

Inspect session results, events, and artifacts

Use DeepSeek Harness to call the runtime

Supported clients

DeepSeek HarnessFull support

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