fim-one

MCP server · GitHub · ★ 1.6k · graded 2026-10-28Source linked

Source-available agent platform for Global × China enterprises — wire every system through one agent core. Self-hosted, any LLM.

No outside reports on file

This tool gives an AI agent broad access to your business systems, so secure configuration, strict permissions, and careful monitoring are essential to prevent misuse or data leaks.

Based on public adoption and transparency signals as of Oct 28, 2026. Our opinion, not a code audit or security guarantee.

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What it can access

Local filesNo local folder access notedLOW
Command executionNo shell command runner notedLOW
Network reachConnects to outside service APINOTED
CredentialsRequires API key or tokenREVIEW
Package sourceGitHub (fim-ai/fim-one)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/fim-ai/fim-one ↗

All setup options ↓

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About Fim One

fim-one is a platform that connects multiple business systems through a single AI agent core. It's designed to work with any large language model (LLM) and runs on your own servers rather than in the cloud.

Who it’s for

Enterprise teams in global companies and China-based businesses that need to integrate many different systems. Teams that want to control where their AI runs instead of using cloud-hosted solutions.

Alternatives

LangChain Agents: Open-source framework for building AI agents that interact with tools and APIs
OpenAI Assistants API: Cloud-hosted agent platform with built-in tool integration
AutoGen: Multi-agent conversation framework from Microsoft for complex workflows
Temporal: Workflow engine for orchestrating systems (not AI-focused but similar integration purpose)

Setup

Check these steps against the project’s own instructions before running anything.

Follow the project's README at https://github.com/fim-ai/fim-one (opens external site) for installation and configuration steps. The exact setup depends on your systems and LLM choice.

Why this grade

CC — Moderate risk signals

Signal-based grade (3/7 points): well starred on GitHub, public source code. This reflects adoption and transparency, not a code review.

Popularity and upkeep

35/100

GitHub stars: 1.6k
Listing last refreshed: 2026-10-29

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 2026-10-30).

Check a specific version →

Risks to watch for

System access: The agent can potentially reach any system you connect to it, so misconfiguration could expose databases, APIs, or internal tools to unintended use
Prompt injection: Attackers could craft prompts through connected systems that trick the AI into performing unintended actions or returning sensitive data
LLM relay attacks: Since it works with any LLM, using untrusted or compromised language models could allow attackers to intercept requests and responses
Credentials in memory: API keys and system credentials stored for connections might be exposed if the agent process is compromised or logs are not secured
Chain-of-command confusion: With many systems wired together, it's hard to track which system requested what, making it difficult to audit who did what

How to lower the risk

Least-privilege permissions

Connect only the systems the agent actually needs
Give each connection the minimum permissions required for its specific task

Network isolation

Run the agent on an isolated network segment or within a secure container
Restrict outbound connections to only approved systems

Monitoring

Log all actions the agent takes and which systems it accesses
Set up alerts for unusual requests or failed authentication attempts

Red flags to watch for

Unexpected new systems being added to the agent
Requests that seem unusual or don't match normal business patterns
Errors or timeouts that could indicate tampering

Questions

How do I install Fim One?

Fim One does not publish a standalone npm or PyPI package. Clone or follow the setup instructions in its source repository at github.com/fim-ai/fim-one.

Are there security reports about Fim One?

No reports found for this package in our research (last checked 2026-10-30). Fim One currently holds Grade C (Moderate risk signals) based on public adoption and transparency signals. Key risk areas to watch include system access, prompt injection, llm relay attacks.

Is Fim One actively maintained?

Fim One has 1.6k GitHub stars. Our directory data was last refreshed on 2026-10-29. Check recent commit activity, release tags, and open issues at github.com/fim-ai/fim-one before pinning it in production.

What are alternatives to Fim One?

Notable alternatives to Fim One include LangChain Agents (Open-source framework for building AI agents that interact with tools and APIs), OpenAI Assistants API (Cloud-hosted agent platform with built-in tool integration), AutoGen (Multi-agent conversation framework from Microsoft for complex workflows), Temporal (Workflow engine for orchestrating systems (not AI-focused but similar integration purpose)). You can also compare Fim One side by side with other MCP servers in the Related tools section on this page.

Maintain or use Fim One? Show its live grade in your GitHub README, docs site, or run a check from the terminal before you install.

GitHub README Markdown:

markdown

[![AgentArmorHQ Risk Grade for Fim One](https://agentarmorhq.com/api/badge/fim-ai-fim-one)](https://agentarmorhq.com/skills/fim-ai-fim-one)

HTML embed:

html

<a href="https://agentarmorhq.com/skills/fim-ai-fim-one"><img src="https://agentarmorhq.com/api/badge/fim-ai-fim-one" alt="AgentArmorHQ Risk Grade for Fim One" height="20" /></a>

Terminal check:

terminal

curl -fsSL https://agentarmorhq.com/api/cli | node --input-type=module - check "fim-ai-fim-one"

Share with your security lead

Need sign-off to use fim-one? Copy this note for Slack, a ticket or a pull request.

### AgentArmorHQ Security Review Memo: fim-one
- **Listing URL:** https://agentarmorhq.com/skills/fim-ai-fim-one
- **Type:** App connector
- **Risk Grade:** Grade C (Moderate risk signals)
- **Outside Security Advisories on File:** 0
- **Public Adoption:** 1.6k GitHub stars

#### Permission & Blast-Radius Signals
- **Local files:** No local folder access noted
- **Command execution:** No shell command runner noted
- **Network reach:** Connects to outside service API
- **Credentials:** Requires API key or token
- **Package source:** GitHub (fim-ai/fim-one)

#### Recommended Hardened Setup
- **Source Repo:** https://github.com/fim-ai/fim-one
- **Controls:** Pin an exact version in `.mcp.json`, scope access to a single workspace folder, and use a least-privilege read-only token where supported.

_Based on public adoption and transparency signals as of Oct 28, 2026. Our opinion, not a code audit or security guarantee._

Key facts

Type: App connector
Publisher: fim-ai
Source code: github.com/fim-ai/fim-one
Est. context load: ~850 tokens / turn (~5 tool schemas, 0.43% of 200k context)
Popularity: 1.6k GitHub stars
Last updated: 2026-10-29
Last graded: 2026-10-28

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