deepbot

DeepBot is a system-level, desktop-oriented multi-agent AI assistant (Electron/TypeScript) that supports multi-tab session management, tool execution (files/commands/browser/web search/fetch/memory/scheduling/Feishu doc operations), long-term memory, and external connector integration (notably Feishu). It is packaged to run locally (and via Docker) and uses a path allowlist for file/command access.

Evaluated Mar 30, 2026 (0d ago)
Homepage ↗ Repo ↗ Ai Ml ai-agents desktop electron multi-agent tool-calling automation scheduling memory feishu typescript local-first
⚙ Agent Friendliness
30
/ 100
Can an agent use this?
🔒 Security
50
/ 100
Is it safe for agents?
⚡ Reliability
29
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
0
Documentation
55
Error Messages
0
Auth Simplicity
60
Rate Limits
0

🔒 Security

TLS Enforcement
60
Auth Strength
45
Scope Granularity
50
Dep. Hygiene
40
Secret Handling
55

Documented security mechanism includes a path allowlist/workspace isolation for file/command operations. Auth model keys and connector secrets are configured via .env/connector settings, but there is no explicit documentation of TLS/transport security details for local services, secret storage hygiene (e.g., vault vs plaintext), or fine-grained permission scopes for tools/operations. Dependency list includes general server/web packages and key JWT usage; without audit/CVE status in provided content, dependency hygiene is uncertain.

⚡ Reliability

Uptime/SLA
0
Version Stability
40
Breaking Changes
30
Error Recovery
45
AF Security Reliability

Best When

When teams want a local, tool-using AI desktop/workflow system that can coordinate multiple agents and automate routine office tasks with a configured workspace allowlist.

Avoid When

When you cannot safely allow tool access to the host filesystem/command execution surface, or when you need a clearly specified, externally callable API contract (REST/OpenAPI) for programmatic agent integration.

Use Cases

  • Internal knowledge work automation (document processing, summarization, research)
  • Multi-step workflows across teams/departments via multiple cooperating agents
  • File-backed productivity: read/write within an allowed workspace, store and reuse memory
  • Scheduled automations (cron-style jobs) with execution history
  • Feishu integration for chat-based assistance and Feishu document operations
  • Building/combining Skills to create reusable, tool-using workflows

Not For

  • Running as an untrusted public-facing API service without hardening
  • Highly regulated deployments that require formal compliance attestations and detailed security documentation
  • Use cases requiring guaranteed idempotent side effects across retries unless the specific tools are designed for it
  • Environments where granting local command execution/file access is not acceptable

Interface

REST API
No
GraphQL
No
gRPC
No
MCP Server
No
SDK
No
Webhooks
No

Authentication

Methods: Local configuration of model API keys (Ali Qwen/OpenAI/Claude) Feishu connector configuration (App ID/App Secret; robot pairing/authorization)
OAuth: No Scopes: No

No explicit OAuth flow or first-class API auth described; authentication is mainly via local API keys for model providers and connector credentials for Feishu.

Pricing

Free tier: No
Requires CC: No

README describes no product pricing; costs would primarily be external LLM/provider usage and any connected services (e.g., Feishu, Tavily, Gemini).

Agent Metadata

Pagination
none
Idempotent
False
Retry Guidance
Not documented

Known Gotchas

  • No documented public API/MCP contract for agents to call programmatically; interaction is via the desktop UI/IPC/websocket/connectors.
  • Tool surface includes command execution and browser automation; an agent must respect the path allowlist and any additional safety policies.
  • Scheduling and multi-agent coordination may require careful handling to avoid duplicate actions; doc only mentions anti-duplicate for Feishu messages, not global idempotency for all tools.

Alternatives

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Scores are editorial opinions as of 2026-03-30.

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