apflow
**AI-Perceivable Distributed Orchestration** apflow is a distributed task orchestration engine where every capability is AI-perceivable — discoverable, understandable, and invocable by AI agents through the apcore module standard.
No outside reports on file
apflow is distributed via GitHub (aiperceivable/apflow); review its source code, dependencies, and requested permissions before use.
Based on public adoption and transparency signals as of Oct 19, 2026. Our opinion, not a code audit or security guarantee.
What it can access
- Local filesNo local folder access notedLOW
- Command executionNo shell command runner notedLOW
- Network reachLocal or standard API callsLOW
- CredentialsNo API token requiredLOW
- Package sourceGitHub (aiperceivable/apflow)PUBLIC
Inferred from this listing’s public package details and description. Check the project’s source before installing.
Install
No npm or PyPI package is listed. Install from source: github.com/aiperceivable/apflow ↗
About Apflow
Apflow is an MCP server focused on General: AI-Perceivable Distributed Orchestration apflow is a distributed task orchestration engine where every capability is AI-perceivable — discoverable, understandable, and invocable by AI agents through the apcore module standard.
It is hosted on GitHub at aiperceivable/apflow (9 GitHub stars). Based on its public metadata, it operates with standard local or API scope without broad shell execution flags noted.
Setup
These use the package this listing points to. Check the project’s own instructions before running anything.
No npm or PyPI package is listed for this MCP server. Source code and setup steps: github.com/aiperceivable/apflow.
Why this grade
Signal-based grade (1/7 points): public source code. This reflects adoption and transparency, not a code review.
Popularity and upkeep
- GitHub stars
- 9
- Listing last refreshed
- 2026-10-21
These are public popularity signals, not a maintenance check. Look at the repository’s commit history and open issues.
Security reports
No reports found for this package in our research (last checked 2026-10-29).
Risks to watch for
- Dependency & version pinning: Distributed via GitHub (aiperceivable/apflow). Pin an exact release version or commit SHA rather than floating tags so upstream updates are reviewed first.
How to lower the risk
Least-privilege permissions
- Give it access only to the specific folders, accounts or projects it needs, never your whole drive or admin account.
- Use a separate, limited API key or login just for this tool so you can switch it off without affecting anything else.
Network isolation
- Run it on a work computer or sandbox account, not one holding personal or company-sensitive data.
- If your IT team can, limit which websites and services it is allowed to contact.
Monitoring
- Check its activity history or logs weekly at first, and look at what it changed or sent.
- Turn on alerts for new logins or unusual usage on any account it connects to.
Red flags to watch for
- It asks for more access than its job requires, or prompts you to paste passwords.
- It suddenly updates with new owners, or starts contacting unfamiliar websites.
Questions
How do I install Apflow?
Apflow does not publish a standalone npm or PyPI package. Clone or follow the setup instructions in its source repository at github.com/aiperceivable/apflow.
Are there security reports about Apflow?
No reports found for this package in our research (last checked 2026-10-29). Apflow currently holds Grade D (High risk signals) based on public adoption and transparency signals. Review the permissions and source repository before granting access to local files, shell commands, or API keys.
Is Apflow actively maintained?
Apflow has 9 GitHub stars. Our directory data was last refreshed on 2026-10-21. Check recent commit activity, release tags, and open issues at github.com/aiperceivable/apflow before pinning it in production.
What are alternatives to Apflow?
Compare Apflow side by side with similar MCP servers in the Related tools section on this page, or browse all MCP servers on AgentArmorHQ.
Key facts
- Type
- App connector
- Publisher
- aiperceivable
- Source code
- github.com/aiperceivable/apflow
- Est. context load
- ~900 tokens / turn (~5 tool schemas, 0.45% of 200k context)
- Popularity
- 9 GitHub stars
- Last updated
- 2026-10-21
- Last graded
- 2026-10-19
Community
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