fineract-agent-skill

fineract-agent-skill is a skill for Claude Code, Codex from openMF/mcp-mifosx. It costs 103 tokens per session (1,748 once invoked), scanned A, original, MPL-2.0.

A skill for working with Apache Fineract, a banking system that provides a REST API for applications to manage financial data and operations.

In plain words
What is it for?
It is for managing clients, loans, savings accounts, groups, charges, accounting records, staff, offices, products, and reports in a Fineract-powered system.
Why use it?
It gives an agent a structured way to carry out banking tasks instead of requiring each operation to be implemented through separate manual API requests.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It is for managing clients, loans, savings accounts, groups, charges, accounting records, staff, offices, products, and reports in a Fineract-powered system.

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Install with agentmods
npx agentmods add skills/openmf/mcp-mifosx/mifos-agent
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add openMF/mcp-mifosx --skill mifos-agent
Clone the repo
git clone --depth 1 https://github.com/openMF/mcp-mifosx

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for fineract-agent-skill

README.md
[![agentmods](https://agentmods.dev/badge/skills/openmf/mcp-mifosx/mifos-agent/github.svg)](https://agentmods.dev/skills/openmf/mcp-mifosx/mifos-agent)
Your own site
<a href="https://agentmods.dev/skills/openmf/mcp-mifosx/mifos-agent"><img src="https://agentmods.dev/badge/skills/openmf/mcp-mifosx/mifos-agent/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for fineract-agent-skill

Your own site · 80×15
<a href="https://agentmods.dev/skills/openmf/mcp-mifosx/mifos-agent"><img src="https://agentmods.dev/badge/skills/openmf/mcp-mifosx/mifos-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 103 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,748 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00103 $0.01748
Opus 5.5 $0.00041 $0.00699
Sonnet 5.5 $0.00021 $0.00350
Haiku 4.5 $0.00010 $0.00175

Measured 6d ago against content hash 930236876bcd, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

fineract-agent-skill scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

The scan reads SKILL.md. This mod also ships 15 executable files (fineract_skill/__init__.py, fineract_skill/client.py, fineract_skill/domains/__init__.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agent-skill/mifos-agent/SKILL.md · 116 lines

How it starts

The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Apache Fineract Agent Skill

Provides 55+ tools across 9 domains for full-lifecycle banking operations against an Apache Fineract instance.

Prerequisites

  1. Verify the environment file exists at agent-skill/mifos-agent/.env. If missing, copy agent-skill/mifos-agent/.env.example and populate the credentials. See references/environment-config.md for variable descriptions.
  2. Verify the Python package is installed: pip install -e agent-skill/mifos-agent/.[dev]. If import errors occur, re-run this command.

Step 1: Initialize the Client

  1. Import and instantiate the Fineract client:
    from fineract_skill import FineractClient
    client = FineractClient()
    
  2. Verify connectivity by calling client.ping(). If the result contains "status": "error", inspect the error message and check the .env configuration.

Step 2: Discover Available Tools

  1. Import the tool registry:
    from fineract_skill import list_tools, get_tool
    
  2. To list all tools: list_tools(). To filter by domain: list_tools(domain="loans").
  3. Supported domains: clients, loans, savings, groups, accounting, staff, products, charges, reports.
  4. For the full tool catalog with parameter schemas, read references/tool-catalog.md.

Step 3: Execute a Tool

  1. Look up the tool by name: tool = get_tool("search_clients").
  2. Call the handler, passing the client as the first argument followed by the required parameters:
    result = tool.handler(client, name_query="John")
    
  3. All tools return a standardised envelope:
    • Success: {"ok": True, "data": {...}}
    • Failure: {"ok": False, "error": "..."}
  4. If result["ok"] is False, read the error field. Common causes: invalid IDs, missing required fields, or authentication failures.

Step 4: Export Schemas for Agent Frameworks

  1. For OpenAI function-calling format:
    from fineract_skill.tools import get_openai_tools
    schemas = get_openai_tools()
    
  2. For MCP-compatible format:
    from fineract_skill.tools import get_mcp_tools
    schemas = get_mcp_tools()
    
  3. For the static JSON schema template, read assets/tool-schema-template.json.

Read the full file on GitHub · 116 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 116 lines · 103 tokens per session scan A 930236876bcd

Subscribe to this mod's changes

fineract-agent-skill is a skill published in the GitHub repository openMF/mcp-mifosx (26 stars, last pushed today), licensed MPL-2.0. It adds 103 tokens to every session and 1,748 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-10.

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