Blog Kalinotes - May 2026

MCP connectors (Model Context Protocol) now allow your AI assistant to read and write directly into your Kalinotes projects. Combined with Claude Code skills, they turn note-taking, application review, and bug tracking into fully automated workflows — without leaving your terminal or IDE.

What is the MCP protocol?

The Model Context Protocol (MCP) is an open standard developed by Anthropic that allows AI agents to connect to external data sources and tools in a standardised way. In practice, instead of manually copying and pasting content between your assistant and your tools, the MCP connector creates a direct bridge: the AI can read your notes, create new content and update existing entries in real time.

Kalinotes provides its own MCP connector that gives access to your entire workspace: projects, categories, notes and comments. Your AI therefore has the same context as you, with no extra effort.

Setting up the Kalinotes MCP connector

The setup takes three steps from your terminal:

1. Install Claude Code: npm install -g @anthropic-ai/claude-code
2. Retrieve your API token from your Kalinotes account settings
3. Add the MCP server to Claude Code: claude mcp add kalinotes --token YOUR_TOKEN

Once configured, Claude Code has access to all your Kalinotes projects and categories. You can verify the connection by asking Claude: "List my Kalinotes projects".

The 8 available Claude skills for Kalinotes

Skills are slash commands (Markdown files placed in ~/.claude/commands/) that extend Claude Code's capabilities with specialised workflows. Kalinotes offers eight dedicated skills, downloadable from the app.kalinotes.com/outils/claude-skills page.

Installing skills

Each skill comes as an .md file to be placed in ~/.claude/commands/ for global availability, or in .claude/commands/ at project level for local scope. Once in place, the corresponding slash command is immediately available in any Claude Code session.

Use case: full application review with /kalinotes-qa

Here is a concrete scenario illustrating the power of the MCP + skills combination. You have just finished developing a web application and want to carry out a quality review before delivery, generate bug and improvement notes, consult a summary report, and share the results with your client or team.

Step 1 — Connect your AI and install the skills

After configuring the MCP connector as described above, download the skills from the Kalinotes tools page. Copy the kalinotes-qa.md and kalinotes-bug.md files into your ~/.claude/commands/ folder. Then open Claude Code in your project directory:

Step 2 — Launch the QA review with /kalinotes-qa

Start the audit by providing your application's URL (or the local path if it is running in development):

/kalinotes-qa https://my-app.example.com

Claude Code then goes through the application along four axes of analysis:

• Functional: verification of user journeys, forms, links, navigation
• UX: visual consistency, accessibility, readability of error messages
• Performance: load times, unoptimised images, blocking resources
• Security: missing HTTP headers, exposed sensitive data, risky configurations

Step 3 — Generate bug and improvement notes

At the end of the audit, Claude automatically creates structured notes in your Kalinotes project. Each detected anomaly generates a bug note via /kalinotes-bug, including:

• The description of the observed symptom
• Steps to reproduce the issue
• Estimated severity (blocker, major, minor)
• A suggested fix

Improvement points (UX, performance, accessibility) are saved in a dedicated "Improvements" category, with a priority rating and the expected benefit for the end user.

Step 4 — View the summary report

Once the notes are created, use the /kalinotes-review skill to generate a consolidated project report:

/kalinotes-review

Claude aggregates all the project's notes and produces a structured summary:

• Number of bugs by severity
• Prioritised list of improvements
• Recap of any technical decisions made
• Estimated correction workload

This report can be shared directly with your client or project manager as a record of the acceptance testing phase.

Step 5 — Share project access

Kalinotes lets you share a project with other users from the web interface. Go to the settings of the relevant project and invite your collaborators by email address. You can set two access levels:

• Read-only: ideal for a client who follows progress without modifying notes
• Collaborator: full access for a team member participating in the review

Invited members can access the notes created by your AI directly without needing to install Claude Code or configure the MCP — collaboration stays smooth even for non-developers.

Why this approach is a game changer

The MCP + skills combination eliminates the most time-consuming manual steps of the review cycle: entering bugs, organising notes, writing the report. The AI handles the documentation while you focus on decisions and fixes. And since everything is centralised in Kalinotes, feedback remains accessible, traceable and shareable, regardless of team size.