Blog writing can be tedious and time-consuming — especially when it requires up-to-date research, clear structure, and a consistent tone. Even with AI tools, the process often breaks down: either the content lacks depth, or it loses focus halfway through.
But by combining Perplexity Search and Sequential Thinking inside TypingMind, you can build a writing agent that doesn’t just generate text — it actually thinks through the structure, context, and argument the way a human writer would.
In this guide, we’ll show you how to set up a blog-writing AI agent that can take a topic, perform live research, plan an article, and generate a high-quality draft in your style — all inside TypingMind.
What is Model Context Protocol?
Model Context Protocol (MCP) is a framework that allows AI systems to interact with external resources — such as files, databases, APIs, and other software.
Traditionally, AI assistants only respond to user prompts based on the immediate conversation. They cannot “see” or “touch” external data unless explicitly provided. MCP solves this by enabling:
- External Connections: Letting AI interact with your files, databases, or tools.
- Security and Control: You decide exactly what the AI can access and what actions it can perform.
- Extensibility: Different MCP servers allow different types of interactions, from reading local files to managing cloud data.
Learn more about Model Context Protocol.
What is TypingMind?
TypingMind.com is the best chat UI that help you harness the full potential of ChatGPT and other AI models so you can get the well-shaped AI responses that specifically tailor for your needs.
It offers advanced features such as multiple AI models conversation, chat management (Projects, Folders), plugin integrations, multiple AI agents, and fine-tuned controls for connecting external data and services. TypingMind allows deeper customization, including connecting to MCP servers.
Why Use Sequential Thinking for Blog Writing
Most AI writing tools operate in one-shot prompts: you ask for a blog post and receive a long block of text. The output might be coherent, but it rarely follows a strong logic or structure. That’s because the model is generating all at once — not reasoning through each part of the article.
Sequential Thinking solves this by breaking down the process step-by-step:
- What is the hook?
- What problem are we addressing?
- What’s the core argument and supporting proof?
- How should the article end?
When paired with Perplexity Search for real-world research, you get both credible and logical content.
Step-by-Step to Build This Blog-Writing Agent
Step 1: Enable Required Tools in TypingMind
Before you create the agent, ensure the following are set up:
- Perplexity Search Plugin
- Sequential Thinking MCP Server
If you haven’t installed the Sequential Thinking server yet, add the following JSON to your MCP settings:
{
"mcpServers": {
"sequential-thinking": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-sequential-thinking"
]
}
}
}Then, enable both tools under Settings → Plugins.
Detail setup for:
Step 2: Create a Blog Writing Agent
Now, create a new Agent in TypingMind.
AI Agent name: Blog Writing Agent
Custom instruction for the Agent:
You are an AI writing assistant trained to write blog articles in my personal style.
Your primary task is to write high-quality blog articles about AI tools, news, and trends. I will provide a topic, and you will:
- Use Perplexity Search to research the topic, gathering recent insights, facts, and examples from trusted sources.
- Use the Sequential Thinking plugin to create a well-structured blog outline based on that research. This step is required to ensure the article follows a clear and logical narrative.
- Once I confirm the outline, expand it into a complete article, strictly following my writing style as defined in the attached Training Files.
If you’ve written blog posts before, attach 2–3 of them as Training Files inside TypingMind. This allows the assistant to better match your tone and style.
Step 3: Assign Plugins to the Agent
In the agent config screen, add:
- Perplexity Search Plugin – for live research
- Sequential Thinking (MCP) – for outline generation
You now have an agent that can research, reason, and write.
Step 4: Test the Agent with a Real Topic
Topic: Securing the Model Context Protocol: Building a Safer Agentic Future
Step 1: Research with Perplexity Search
The agent starts by running a query like:
Securing Model Context Protocol in AI agent systems latest news best practicesThe expected Perplexity summary might include:
**Latest Developments in MCP Security**
The Model Context Protocol (MCP) underwent updates in March 2025, finalizing a new version to enhance interoperability and security for AI-agent interactions with external tools and data sources[1][4].
**Core Security Best Practices**
1. **Network Isolation**: Restrict MCP server access to trusted networks to minimize exposure[5].
2. **Input Validation**: Sanitize and validate data inputs from MCP clients to prevent prompt injection attacks[5].
3. **Authentication**: Enforce strict authentication (e.g., OAuth, API keys) for MCP client-server interactions[3].
4. **Least-Privilege Access**: Grant MCP servers only the permissions they require to perform their specific tasks[5].
5. **Logging & Auditing**: Monitor all MCP interactions to detect unauthorized access or malicious activity[3].
**Advanced Safeguards**
- **Output Filtering**: Validate responses from MCP servers to block malicious payloads[5].
- **Rate Limiting**: Throttle excessive tool calls to prevent abuse[5].
- **Secure Token Management**: Use short-lived tokens instead of long-term credentials[5].
**Key Risks**
- **Credential Exposure**: Protect against leaks in MCP client implementations[5].
- **Malicious Servers**: Vet third-party MCP servers for security compliance[3][5].
- **Prompt Manipulation**: Mitigate risks of adversarial prompts exploiting MCP tools[5].
**Implementation Tips**
- **Client-Server Segmentation**: Use separate MCP servers for distinct capabilities (e.g., file access vs. API calls) to limit breach impact[3][5].
- **Protocol Version Control**: Enforce MCP versioning to exclude outdated or insecure implementations[5].
These practices address MCP's expanded attack surface while enabling secure AI-agent tool interactions[3][5].
Step 2: Generate Outline with Sequential Thinking
The agent now sends the research summary to Sequential Thinking MCP server so it can have multiple steps of thinking:
This allows your blog has a hook and a persuasive outline that can lead your customer’s thought while reading.
Step 3: Expand the Blog Post to Write a Complete Article
Now, if you do not need any further modification, the AI assistant uses this outline to write the full article.
You can view the full article here on TypingMind.
Without Sequential Thinking, the agent tends to produce content that often lacks cohesion, depth, and flow — making it feel like stitched-together paragraphs rather than a guided argument.
With Sequential Thinking, the agent breaks the writing task into logical steps, ensures every section serves a purpose, and maintains clarity from intro to conclusion. The difference isn’t just in structure — it’s in how the content makes sense to the reader, one step at a time.
Beyond Blog Writing
Beyond blog writing, TypingMind also helps you integrate with multiple platforms to improve your daily workflow:
- Automate Task Creation in Linear from Figma Designs
- Build and Deploy a Full Website Using TypingMind MCP and Github
- Automatically Organize Download Files with TypingMind and FileSystem MCP
The possibilities are endless. Try now on TypingMind!
Final Thoughts
Writing blog posts no longer needs to be a slow, manual process. With this Agent, you can move from idea to publication in minutes, without sacrificing depth or quality.
By building a TypingMind agent using Perplexity Search and Sequential Thinking, you’re not just saving time — you’re creating a repeatable system that can scale with your content strategy.
