Blog
Notes on MCP, AI agents, and context management.
-
June 6, 2026
Internal Knowledge Base AI: Build or Connect?
Internal knowledge base AI explained: when to build a dedicated AI knowledge base vs connect AI to your existing sources, with a clear decision checklist.
-
June 6, 2026
What Is Agent Context? A Plain-English Guide
What is agent context? It's everything an AI agent sees in a single call. Learn what's in it, why it matters, and how it shapes answers.
-
June 6, 2026
What Is AI Memory? A Clear Definition
AI memory is information an AI retains across sessions, stored outside the model and recalled later. Here's what it is and how it works.
-
June 5, 2026
Scoped Memory for AI Agents: Recall Only What Matters
Scoped memory for AI agents means recalling only what's relevant to the task, person or project. Learn the scoping patterns that keep agents sharp.
-
June 5, 2026
How Do AI Agents Remember? The Mechanics Explained
AI agents remember by writing useful facts to a persistent store and retrieving the relevant ones later. Here's how the memory loop actually works.
-
June 5, 2026
MCP vs RAG: How They Fit Together
MCP vs RAG, explained: RAG is a technique for finding relevant text; MCP is a connection standard. See how they complement each other, with a comparison table.
-
June 5, 2026
Lost in the Middle: How LLMs Drop Context
Lost in the middle is when LLMs ignore facts buried in long prompts. Learn why models attend to the edges and how to keep key facts in view.
-
June 4, 2026
Sharing Context Across ChatGPT, Claude and Cursor
Multi-tool AI context sharing lets ChatGPT, Claude and Cursor read the same company knowledge from one connection. Here's how cross-tool context works.
-
June 4, 2026
Team Knowledge for AI Assistants: One Shared Layer
How to make team knowledge available to AI assistants across people and tools — so everyone gets the same scoped, current answers from one shared layer.
-
June 4, 2026
AI Memory vs Context: What's the Difference?
AI memory persists across sessions; context is what the model reads on one request. Here's the difference, with a clear comparison table.
-
June 4, 2026
Give Cursor Your Company's Codebase Context
How to give Cursor your company's codebase context: connect docs, decisions, and conventions via MCP so the editor codes to your standards.
-
June 3, 2026
Context Pruning for AI Agents: Curate, Don't Dump
Context pruning for AI agents means removing stale, irrelevant tokens before each call. Learn the techniques that keep agents accurate, fast and cheap.
-
June 3, 2026
Long-Term vs Short-Term Memory for LLMs: The Brain Analogy
LLMs benefit from the brain's split: short-term working memory for the task, long-term memory for durable facts. Here's how the analogy works.
-
June 3, 2026
The "Plaid of Context": One Connection, Every AI Tool
The "Plaid of context" means one connection that links your company knowledge to every AI tool — the way Plaid links apps to banks. Here's the idea.
-
June 3, 2026
Context Engineering: The Discipline Behind Reliable AI
Context engineering is the practice of deciding what an AI agent sees per call. Learn the principles that make AI agents accurate and reliable.
-
June 2, 2026
MCP for Company Knowledge: The Unified Context Layer
MCP for company knowledge lets AI tools read your team's docs, wikis and files directly. Here's how the unified context layer works and why it matters.
-
June 2, 2026
Context for Cursor: Beyond the Open Files
Context for Cursor goes beyond the open files. Learn how to feed the editor your company's knowledge via MCP so it codes like a teammate.
-
June 2, 2026
What Is MCP in AI? A Plain-English Explainer
MCP in AI is an open standard that lets AI tools connect to your data and actions. Here's what MCP means, where it came from and why it matters.
-
June 2, 2026
MCP for Dummies: The No-Jargon Intro
MCP for dummies: a no-jargon intro to the Model Context Protocol — what it is, why it exists and how it lets AI tools use your data. Plain English.
-
June 1, 2026
MCP vs API: What's the Difference?
MCP vs API, explained: an API is a custom interface per service; MCP is one open standard that wraps many. See the differences in a clear comparison table.
-
June 1, 2026
How Does an MCP Server Work? A Clear Walkthrough
An MCP server works by exposing data or actions over the Model Context Protocol so AI tools can query them. Here's the request flow, step by step.
-
June 1, 2026
ChatGPT and Company Knowledge: Approaches Compared
ChatGPT and company knowledge: compare prompts, custom GPTs, and standardized context layers like MCP to give ChatGPT access to your internal information.
-
May 31, 2026
AI Context Management for SMBs: A Practical Guide
AI context management for SMBs means connecting company knowledge to your AI tools once, scoped and shared. Here's how small teams do it without engineers.
-
May 31, 2026
Connect AI to Internal Company Knowledge: A Playbook
How to connect AI to internal company knowledge: a step-by-step playbook covering inventory, scoping, method choice, and standards like MCP. Start scoped.
-
May 31, 2026
A Context Layer for All Your AI Tools
A context layer for AI tools is one connection that feeds your company knowledge to every AI surface — Claude, ChatGPT, Cursor. Here's how it works.
-
May 31, 2026
MCP for Business Users: AI on Company Knowledge, No Code
An MCP server for business users with no coding lets non-technical teams query company knowledge from their AI tools. Here's how it works in practice.
-
May 30, 2026
The Unified Context Layer for AI: What It Is
A unified context layer for AI is one shared, scoped, persistent source of company knowledge that every AI tool can query. Here's why it matters.
-
May 30, 2026
Shared AI Memory for Teams: One Brain for the Company
Shared AI memory lets a whole team's AI tools draw on the same persistent knowledge. Here's how it works and why it beats per-person memory.
-
May 30, 2026
How to Give Claude Access to Company Documents
How to give Claude access to your company documents: compare prompts, projects, and standardized context layers like MCP, and pick the safe, scalable path.
-
May 30, 2026
MCP for Documentation: Let AI Search Your Docs
An MCP server for documentation lets AI tools search and read your docs directly. Here's how it works and how to set up doc access the right way.
-
May 29, 2026
Context Management for Claude Code
Context management for Claude Code keeps the agent accurate as tasks grow. Learn what to include, prune, and connect via MCP for reliable output.
-
May 29, 2026
Company Knowledge Base for an AI Assistant: Build vs Connect
Building a company knowledge base for an AI assistant vs connecting one: how the two approaches compare on effort, freshness, permissions, and scale.
-
May 29, 2026
How to Give AI Access to Your Company's Knowledge
How to give AI access to company knowledge: every method compared, from prompts and projects to standards like MCP. Pick the right approach for your team.
-
May 29, 2026
What Is an MCP Server? A Plain-English Guide for Teams
An MCP server is a bridge that lets AI tools read your data through one open standard. Here's what it is, how it works and why teams use it.
-
May 28, 2026
How to Give AI Access to Your Files, Safely
How to give AI access to your files safely: compare uploading, projects, and live context layers like MCP, and apply scope and permission guardrails first.
-
May 28, 2026
MCP Servers, Explained Simply
MCP server explained: what it is, how it connects AI tools to your data, and why teams use it. A simple, jargon-light walkthrough of the basics.
-
May 28, 2026
How to Use MCP Without Coding: A Plain Guide
Learn how to use MCP without coding. A step-by-step guide for non-technical teams to query company knowledge from AI tools — no scripts required.
-
May 28, 2026
How Does MCP Work? A Step-by-Step Walkthrough
How does MCP work? A step-by-step walkthrough: connect, negotiate, discover, request, fetch and answer — the full Model Context Protocol flow in plain English.
-
May 27, 2026
Persistent Memory for AI Agents: A Practical Guide
Persistent memory lets AI agents retain knowledge across sessions. Learn how it works, why it beats bigger context windows, and how to design it.
-
May 27, 2026
How to Choose an MCP Server for Coding
How to choose an MCP server for coding: the criteria that matter — scoping, permissions, freshness, and multi-surface support for your AI tools.
-
May 27, 2026
What Is an MCP Server Used For? Real Uses
An MCP server is used to let AI tools read your data and take actions through one standard. Here are the main uses, with concrete examples.
-
May 26, 2026
Does More Context Improve LLM Answers?
Does more context improve LLM answers? Only up to a point — then it backfires. Learn where the curve turns and how to give the right amount.
-
May 26, 2026
Context for Claude Code: Feed It Company Knowledge
Context for Claude Code means more than open files. Learn how to feed coding agents your company's knowledge via MCP, scoped and on demand.
-
May 26, 2026
Context Window Management for AI Agents
Context window management is how you budget tokens across instructions, history, and data. Learn practical tactics to keep AI agents accurate.
-
May 26, 2026
MCP Server for Teams: Company Knowledge, Not Just Chat
An MCP server for teams turns AI from a personal chatbot into shared company knowledge. See how team-wide context works and why it beats individual chats.
-
May 25, 2026
Why Your AI Gives Generic or Wrong Answers
AI gives generic or wrong answers when it lacks the right context. Learn the real causes and how to ground your AI in your actual knowledge.
-
May 25, 2026
MCP Server Architecture: JSON-RPC, Transports, Primitives
MCP server architecture, explained: the host-client-server model, JSON-RPC 2.0 messages, stdio and Streamable HTTP transports, and the core primitives.
-
May 25, 2026
MCP Context in Cursor: Setup and Patterns
MCP context in Cursor lets the editor pull company knowledge on demand. Learn the setup, configuration, and patterns that keep context scoped.
-
May 25, 2026
AI That Remembers Across Sessions: How It Works
AI memory across sessions means an assistant recalls past conversations instead of resetting. Here's how persistent recall works and why it matters.
-
May 24, 2026
MCP Server Meaning: Definition + Example
MCP server meaning, explained: a connector that lets any AI tool read your data through one open standard. Plain definition, a clear example and FAQs.
-
May 24, 2026
MCP vs Tools vs Agents: Clearing Up the Terms
MCP vs tools vs agents, explained: tools are what a model can call, an agent is the loop that decides, MCP is how tools get delivered. Clear table + FAQs.
-
May 24, 2026
How Much Context Does an AI Agent Need?
How much context does an AI agent need? Not too little, not too much. Learn the Goldilocks middle path that keeps agents accurate and cheap.
-
May 24, 2026
MCP Server Directory: Find the Right One for You
An MCP server directory helps you discover and evaluate servers for your stack. Learn where to look, what to check, and how to pick the right one.
-
May 23, 2026
MCP Servers for Business: What They Unlock for Teams
An MCP server for business connects your AI tools to company knowledge. See what MCP servers unlock for non-technical teams and how to evaluate one.
-
May 23, 2026
Context Rot: Why More Context Can Make AI Worse
Context rot is when AI accuracy drops as input grows — well before the window fills. Learn why it happens and how to avoid it in your agents.
-
May 23, 2026
AI Agent Memory: Persistent, Scoped Context Explained
AI agent memory is context that persists across sessions, is scoped like the human brain, and can be shared across a team. Here's how it works.
-
May 23, 2026
Secure AI Access to Company Data
Secure AI access to company data: the guardrails that matter — scope, permissions, freshness, and auditability — plus how standards like MCP centralize them.