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openMF/mcp-mifosx

openMF/mcp-mifosx

☁️ 🏠 - Core banking integration for managing clients, loans, savings, shares and transactions, and generating…
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add mcp-mifosx -- npx -y mcp-mifosx
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
26 ★ · openMF/mcp-mifosx · 取自该仓库的 GitHub 页面 · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 10 个来源列出
评分构成
综合分 1,003 · 26 ★ · 10 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 openMF/mcp-mifosx;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

Mifos MCP - Model Context Protocol (MCP)

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

This project provides Model Context Protocol (MCP) for the Mifos X Ecosystem, enabling AI agents to access financial data and operations.
Implementations are available in:
- **Go (Native)** — 102 typed tools (high-performance, cloud-native with SSE/Stdio).
- **Java (Quarkus)** — 38 typed tools (across Backoffice and Recommendations).
- **Python (FastMCP)** — 49 typed tools (modular domain-driven design).
- **Rust** — 89 typed tools (high-performance async I/O with exclusive bulk operations).
---
Architecture Overview
The Mifos MCP Server acts as a standalone, stateless integration tier that bridges any AI assistant or agent framework to the **Apache Fineract** banking backend.
This repository is **framework-agnostic**. The client (LLM brain, UI, memory) lives in a separate repository. Any MCP-compatible system can plug in.
---
Agentic Platform Architecture
The Agentic Gateway builds on these MCP servers to replace the plain LLM gateway behind the Mifos X WebApp copilot with an agent harness running a swarm of specialized agents.
- **User channels** — Mifos WebApp (Chat / Copilot UI), Mifos Pay, Mifos Mobile, Mifos Field Officer and Mifos Web Banking. The **Agent CLI** is an optional entry point for developers and power users.
- **Agentic Gateway** — reuses the existing Mifos AI Gateway endpoint, but routes requests to an agent harness instead of directly to an LLM.
- **Agent Harness** (runtime for Pi / Prime / Hermes) — wraps every agent with the LLM model provider, an LLM firewall (safety & security), observability (logging / monitoring) and session management (tool orchestration).
- **Specialized Agents** — Enrollment Agent, KYC/FT Reviewer, Loan Reviewer, Scoring Reviewer, Document Reviewer and others. Their Fineract tool calls use the calling officer's credentials and permissions; agents do not have separate Fineract roles.
- **MCP Tools / AG-UI compatible tools** — Fineract, loan, client, product, workflow, reporting and custom tools, invoked as needed by the agents.
- **Apache Fineract + Grants / RBAC** — the core banking backend. Fineract enforces grants for the authenticated officer: if the officer's role has the required grant, the call (including write APIs) succeeds; otherwise, it is denied.
- **External Systems** (via tools) — Scoring, Black List, Sanction List, National ID, Identity Verification and Biometrics systems.
---
Implementation Synchronization
While this repository hosts two different programming languages, they are kept in **functional parity** where possible to ensure a consistent experience.
How they "Sync":
1. **Tool Specification**: All implementations aim to expose the same core banking tools.
- **Go** currently leads with **102 tools**, featuring advanced cloud-native features and SSE.
- **Rust** provides **89 tools**, uniquely featuring high-concurrency Bulk Operations and robust "Fetch-and-Merge" state management.
- **Python** provides **49 tools** using a modular domain design.
- **Java** provides **38 tools** (21 for Backoffice operations and 17 for User Recommendations).
2. **API Alignment**: All implementations are built against the same **Apache Fineract REST API**. They share identical logic for field routing.
3. **Stateless Parity**: All implementations follow a strictly **stateless** design. None of the servers store user data, PII, or AI memory.
4. **Testing Protocol**: Shared "Smoke Tests" ensure that all implementations return identical, predictable JSON structures to the LLM.
---
Project Structure
This repository is structured to support multiple implementations and client integrations.
---
Getting Started
来源
awesome · https://github.com/openMF/mcp-mifosx
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