#MCP

Articles about MCP — exploring patterns, best practices, and real-world implementations in production systems.

22 posts tagged with mcp. ← All posts

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Pratik Dhanave · ·6 min read

Tools

In a model-driven agent, tools are everything the agent can actually do — the model supplies the reasoning, the tools supply the capability. Strands makes defining them almost trivial (decorate a Python function) and plugs into MCP's large ecosystem, so equipping an agent well becomes the developer's main lever.

In a model-driven agent, tools are everything the agent can do — the model supplies the reasoning, the tools supply the capability. Strands makes defining them trivial and plugs into MCP, so equipping an agent well is the developer's main lever.

#Strands#AI Agents#Tool Use#AWS#MCP
Pratik Dhanave · ·5 min read

MCP vs A2A: Tools vs Agents

The most common question about the two big agent protocols is which one to use — and the answer is almost always "both," because they solve different problems: MCP connects an agent to its tools, A2A connects an agent to other agents.

The most common question about the two big agent protocols is which to use — and the answer is almost always both, because MCP connects an agent to its tools and A2A connects an agent to other agents.

#AI Architecture#MCP#A2A#AI Agents#AI Engineering#Software Architecture#LLMs
Pratik Dhanave · ·5 min read

A2A and MCP Together

The two protocols people keep pitting against each other are actually two halves of the same architecture — MCP gives an agent its tools, A2A gives it collaborators, and real systems need both.

MCP gives an agent its tools, A2A gives it collaborators, and real systems need both. How the two protocols compose — tools within an agent, agents between — in one architecture.

#A2A#MCP#AI Agents#Multi-Agent Systems#Protocols
Pratik Dhanave · ·6 min read

Shipping MCP Securely to Production

An MCP server can run code and see context on the model's behalf, which makes it powerful and dangerous in equal measure — this is how to deploy one without handing attackers the keys.

An MCP server can run code and see context on the model's behalf. Authentication, prompt-injection and tool-poisoning risks, human-in-the-loop, sandboxing, and a production checklist.

#MCP#AI Security#Security#AI Agents#Python#Prompt Engineering
Pratik Dhanave · ·5 min read

Building an MCP Client

A server is only half the story; the client is what connects to it, discovers its capabilities, and turns a model's intent into real tool calls.

Build an MCP client that launches a server, discovers its tools, and drives them from a language model — the core of what every MCP host does internally.

#MCP#AI Agents#Python#LLMs#Software Engineering
Pratik Dhanave · ·5 min read

Building an MCP Server from Scratch

Everything in the series so far comes together here: a small but complete Model Context Protocol server, in Python, exposing a tool, a resource, and a prompt, runnable and testable in minutes.

Build a complete MCP server in Python with the official SDK — a notes service with a tool, a resource, and a prompt — and test it end to end with the MCP Inspector.

#MCP#AI Agents#Python#Tool Use#Software Engineering#Prompt Engineering#Testing
Pratik Dhanave · ·6 min read

MCP Tools: Giving Agents the Power to Act

Tools are the part of the Model Context Protocol that lets a model do things instead of just talk about them, and their design is what separates an agent that helps from one that flails.

Tools are the MCP primitive that lets a model act. How to define them, the tools/list and tools/call methods, results versus errors, and designing tools a model can actually use.

#MCP#AI Agents#Tool Use#Python#Software Engineering
Pratik Dhanave · ·5 min read

What Is the Agent2Agent Protocol?

Tools are one half of an agent's world and other agents are the other half, and A2A is the open standard that lets agents built by different teams, in different frameworks, discover and delegate to each other as peers.

A2A is the open standard that lets agents built by different teams, in different frameworks, discover and delegate to each other as peers — the agent-to-agent complement to MCP's agent-to-tools.

#A2A#AI Agents#Multi-Agent Systems#Protocols#MCP
Pratik Dhanave · ·6 min read

What Is the Model Context Protocol?

A model is only as useful as the context and tools it can reach, and MCP is the open standard that lets any AI app plug into any tool through one interface instead of a hundred bespoke integrations.

MCP turns the M×N mess of wiring every AI app to every tool into M+N: wrap each system as a server once, make each app a client once, and any app can use any system.

#MCP#AI Agents#Python#LLMs#Software Engineering
Pratik Dhanave · ·6 min read

MCP: Connecting Claude Code to Your Tools

The Model Context Protocol lets Claude Code reach beyond your codebase — into your databases, issue trackers, docs, and services — through a standard, pluggable interface.

The Model Context Protocol lets Claude Code reach beyond the codebase into databases, trackers, docs, and services through a standard interface — what MCP is, how to connect servers, and treating each server as a least-privilege trust decision.

#Claude Code#MCP#Integration#AI#AI Agents#Databases
Pratik Dhanave · ·10 min read

Tools in Microsoft Agent Framework (Python): Functions, Hosted Tools, MCP, Skills & CodeAct

A complete guide to giving a Microsoft Agent Framework agent the ability to act — from a plain Python function the model can call, to provider-hosted sandboxes, remote MCP servers, and higher-level packaging patterns like Skills and CodeAct.

A complete guide to giving a Microsoft Agent Framework agent the ability to act: function tools, provider-hosted tools (code interpreter, file search, web search), local and hosted MCP, plus Skills and CodeAct — with the code and gotchas for each.

#Microsoft Agent Framework#Python#AI Agents#Tools#MCP#Software Engineering
Pratik Dhanave · ·3 min read

Hosting and the Capstone App — Microsoft Agent Framework in Python

Turning agents into a service you can run and expose, then a full DocQA app that ties the whole series together.

Host Microsoft Agent Framework agents with DevUI, A2A, MCP, and AG-UI, then build DocQA — a grounded, cited multi-agent app that ties the whole Python series together.

#Microsoft Agent Framework#Python#AI Agents#Hosting#Multi-Agent#Software Engineering#MCP#Multi-Agent Systems

All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.