惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Microsoft Azure Blog
Microsoft Azure Blog
宝玉的分享
宝玉的分享
博客园 - 【当耐特】
有赞技术团队
有赞技术团队
G
Google Developers Blog
Microsoft Security Blog
Microsoft Security Blog
Apple Machine Learning Research
Apple Machine Learning Research
The Cloudflare Blog
Blog — PlanetScale
Blog — PlanetScale
博客园_首页
L
LangChain Blog
Stack Overflow Blog
Stack Overflow Blog
Last Week in AI
Last Week in AI
Y
Y Combinator Blog
罗磊的独立博客
T
Tailwind CSS Blog
博客园 - 叶小钗
T
The Blog of Author Tim Ferriss
Engineering at Meta
Engineering at Meta
博客园 - 聂微东
博客园 - Franky
B
Blog
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
F
Fortinet All Blogs

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant
Request for Advice on MCP Integration
RISAInfo · 2026-05-29 · via DEV Community

RISAInfo

We are currently exploring potential use cases for MCP integration in a service we recently launched.

RISA PMT is an integrated project management tool that combines chat, kanban boards, Gantt charts, Wiki, and attendance management into a unified platform.

As we are actively developing MCP integration, we are looking for ideas and insights on:

“What kinds of tasks or workflows would you want AI to automate or assist with in your daily operations?”

Below are some ideas that have already been discussed within the RISA development team:

Initial Ideas from the RISA Development Team

  • Aggregate task ticket specifications and in-task chat discussions to support: -- Finalizing requirements -- Defining completion criteria -- Generating test specifications
  • Analyze ongoing task discussions to identify: -- Unanswered questions or neglected requests -- Tasks that are not progressing smoothly
  • Extract and organize specifications from past activities and automatically document them in Wiki
  • Identify related tickets based on bug or issue descriptions
  • Execute web application tests based on test specifications We would greatly appreciate hearing your ideas and perspectives.

The tools we have developed are as follows:
RISA PMT


RISA PMT Features

1. Chat

RISA Chat was designed to address common challenges found in existing communication tools:

  • Important messages getting buried
  • Notification overload leading to missed critical information
  • Delays caused by assumptions like “they must have seen it”

Key Features of RISA Chat

Mentions and CC

In addition to traditional mentions, we introduced a CC function similar to email.
This allows users to prioritize checking only messages they are directly mentioned in, preventing important communications from being buried in high-volume channels.

Notification Control by Mention/CC

Excessive notifications often lead to “notification fatigue,” where users begin to ignore alerts altogether.
By allowing users to disable notifications for CC messages, RISA significantly reduces noise and restores the effectiveness of notifications.

Read/Unread Status Visibility

Users can visually confirm whether their messages have been read.
Since delays are often caused by uncertainty like "they probably saw it," this visibility dramatically reduces communication risks.
All recipients, including CC members, can see read/unread status mutually.

Reply and Reply All

With a single click, reply targets are automatically optimized:

  • The original sender is set as a mention
  • CC participants are preserved in order This eliminates small but repetitive manual tasks.

Send to All (Mention + CC Conversion)

Instead of mentioning everyone, users can:

  • Mention one primary recipient
  • Automatically include all other channel members as CC

Reply Behavior Rules
|Action|Original Sender|Original CC|
|:---|:---|:---|
|Reply|Mentioned in reply|Not included|
|Reply All|Mentioned in reply|Added as CC|

2. Kanban

While it may look like a typical Kanban board, RISA provides comprehensive task management capabilities.

Chat Integrated Within Task Tickets

Each task ticket contains its own dedicated chat channel.
By keeping communication scoped within tasks:

  • Information fragmentation is eliminated
  • Noise in shared channels is significantly reduced
  • Searching for discussions across threads becomes unnecessary

Notification Optimization

Users can disable notifications for CC messages.
Additionally, users can enable notifications only for:

  • Tasks assigned to them
  • New messages in those tasks This reduces workload while ensuring critical messages are not missed.

Visual Updates on the Board

The Kanban board allows users to instantly identify:

  • Newly updated tasks
  • New chat activity Only tasks assigned to the user display notification indicators, reducing unnecessary checks.

What Makes RISA Kanban Different

  • Instantly identify newly updated tasks
  • Advanced filtering for flexible views
  • Visibility of tasks where the user is mentioned or CC’d
  • High-performance rendering for large volumes of tickets
  • Bulk movement of multiple tickets

3. Gantt Chart

For medium to large-scale projects, long-term planning and visibility are essential.
While Kanban is suited for short-term iterations (e.g., sprints), it is not ideal for long-term scheduling.

Key Design Principles of RISA Gantt

  • Handles large volumes of tickets
  • Spreadsheet-like simplicity and intuitive interaction
  • Minimal learning curve
  • Visual identification of delays and status
  • Integration with attendance data (time-off visibility)

Intuitive Operations

Users can easily:

  • Insert, move, or delete rows
  • Adjust timelines
  • Create Epics, Features, and User Stories directly No specialized training is required.

Flexible Filtering

The Gantt chart can be filtered by:

  • Assignee
  • Sprint
  • Priority
  • Date

Examples:

  • Current sprint tasks
  • Tasks for a specific team member
  • Unassigned tickets

Attendance Integration (Risk Visualization)

Time-off data is reflected directly in the Gantt view.
This allows teams to:

  • Identify scheduling risks early
  • Adjust plans proactively

4. List View

As task volume increases, flexible perspectives become essential.
RISA provides four main views:

  • By Status
  • By Assignee
  • By Sprint
  • By Release Each view groups tasks accordingly.

Capabilities of List View

  • Access grouped data from multiple perspectives
  • Save filters and sorting per tab
  • Edit ticket details inline
  • Add Markdown notes (visible only in list view)
  • Color-coded attributes
  • Adjustable font size and spacing The List view is the most frequently used feature in our internal development process.

5. Wiki

RISA Wiki enables real-time collaborative editing with integrated chat per document.
It uses Markdown-based structured documentation, making it highly compatible with AI-generated content.

Wiki Capabilities

  • Tables, images, code blocks, and Mermaid diagrams
  • Markdown-based content creation
  • Context-specific chat per document

Private Wiki for Personal Knowledge Management

In addition to shared documentation, users can maintain private notes.
A common workflow:

  • Paste AI-generated research results directly
  • Organize and refine information

6. Attendance (Time-Off Tracking)

A simple and intuitive way to record and share time-off.
While not a full HR system, it is designed to support scheduling accuracy via Gantt integration.

Key Benefits

  • Record and visualize time-off
  • Avoid “unexpected absence” issues
  • Enable proactive schedule adjustments

Summary

RISA PMT is an integrated platform combining:

  • Chat
  • Kanban
  • Gantt charts
  • List views
  • Wiki
  • Attendance tracking

The benefits of integration can be hard to visualize at first.
However, in our internal projects, we have experienced:
A reduction of 40%–50% in project management overhead

We strongly believe that integrating RISA PMT with AI systems presents significant opportunities.
We would love to hear your ideas on:

  • Daily workflow automation
  • Weekly/monthly process optimization
  • AI-driven decision support Your insights would be greatly appreciated.