Knowledge base built for devs and agents.
Joggr connects your codebase, conversations, and tools to create an always up-to-date knowledge base for your developers and AI agents.
Trusted by Engineers at
How It Works
Your knowledge base on autopilot
Joggr automatically builds and maintains your knowledge base so your team and AI tools always have the context they need wherever they work.
Connect and Generate
Install Joggr on GitHub and connect to your tools like Slack, Jira, and Linear. Joggr analyzes your codebase, conversations, and tickets to automatically build your knowledge base and keep it up-to-date.
Always up-to-date
As code changes and conversations happen, Joggr automatically maintains and updates your knowledge base in real-time, ensuring your team and AI agents always have accurate, up-to-date documentation & context.
Supercharge your agents
Joggr automatically integrates with your coding agents like Claude Code, Cursor, and more. Your agents can access the exact context they need wherever they work, providing more accurate outputs, faster responses, all while using less tokens.
Overview
From scattered knowledge to structured context
Joggr transforms your engineering knowledge into two powerful outputs: human-friendly docs and AI-ready context.
Ingest data from sources
Joggr automatically pulls knowledge from GitHub, Slack, Jira, Notion, Miro, and other tools.
Format and create structured context
Transform scattered information into a unified knowledge base with proper structure and relationships.
Output for devs & agents
Deliver as markdown documentation for developers and provide MCP access for AI agents to use in real-time.
The Problem
MCP alone isn't enough
Connecting AI to your codebase is just the beginning. Without curated context, your agents inherit every piece of outdated, irrelevant, and contradictory information in your system.
Context Rot Poisons AI Outputs
Stale docs, outdated comments, and deprecated patterns don't disappear—they pollute your AI's context. Research shows a single irrelevant file can drop accuracy by 50%. Your codebase has thousands. Without active curation, AI confidently generates wrong code based on wrong context.
Read Chroma ResearchAgents Rebuild Context Every Session
Watch any AI agent work—it spends most of its time searching, reading files, and trying to understand your codebase. Every. Single. Session. Without prebuilt knowledge, agents waste tokens rediscovering the same patterns, standards, and architecture you already know.
You Need to Build Great Context
MCP gives AI access to information. Joggr gives it the right information. We generate docs that live in your codebase and maintain structured context that evolves with your code—so your agents start with knowledge, not a blank slate.
Read Anthropic's GuideCustomers
Above and beyond
Joggr creates remarkable developer experiences that enable success stories, and empowers software teams to ship features fast as 🦆.
We view documentation as a core pillar of the software development process and treat in in the same regard as instrumentation, automated testing, and monitoring. Unlike these other tenets that have a myriad of products, documentation has been vastly under represented.
That's why we are so appreciative of Joggr which is helping to fill that void. By reducing friction and improving discovery we've seen our internal culture of documentation greatly improved which has a direct impact on developer velocity.
Asaf Peleg
Founding Engineer
Kindred
Keeping documentation in sync with code changes was always a challenge, but Joggr has solved this by seamlessly integrating updates with code changes and storing them alongside the code. This has significantly reduced repetitive questions and streamlined the onboarding process for new developers
Sinash Shajahan
Principal Engineer
Time
I feel like Joggr has helped breathe life into our documentation culture. From a feature perspective you can get an alert when a code change (GitHub pull request) might make a document out of date is incredibly helpful in preventing stale docs (which is a good thing when you really need a runbook).
Brooks Johnson
Senior Software Engineer
CommonLit
Joggr makes it easy to keep our system documentation up to date by fitting right into our development workflow. It gives us a simple, central place to search and find information about our code, saving us time and hassle.
Mitch Eatough
Engineering Manager
LeagueApps
We leverage Joggr to document all of our engineering processes and document core portions of our code. The documentation we've built with Joggr has helped us quickly onboard new engineers.
Olamide Akinola
CTO & Co-founder
Mainstack
Integrations
Universal context
Your entire engineering context: code, conversations, tickets, and more available instantly wherever you work.
GitHub
Claude
Cursor
Windsurf
Copilot
Jules
CodeRabbit
Greptile
Devin
Gemini
Augment Code
Amp Code
Sourcegraph
Teams
Slack
Jira
Linear
Confluence
Notion
More
Features
Built for teams shipping with AI
Every feature designed to solve context engineering. From smart filtering to auto-documentation to custom integrations.
Context Without Limits
Joggr delivers exactly what AI needs, when it needs it. No token bloat. No context rot. Just the right information, every time.
Works Everywhere
Native MCP integration with Claude Code, Cursor, Windsurf, and more. Your context flows automatically to every tool you use.
Always Up-to-Date
Real-time sync across code, conversations, and tickets. Your knowledge base updates the moment anything changes in your stack.
Zero Maintenance
Auto-generates missing documentation. Auto-fixes outdated docs on PRs. Your team never touches documentation again.
Extensible Platform
Build custom Slackbots, agents, and workflows on top of Joggr MCP and APIs. Extend Joggr to fit your exact needs.
Universal Context
Search and connect information across GitHub, Slack, Jira, Linear, Confluence. Everything in one place, instantly accessible.
Ready to get started?
Give your team and AI tools the complete context they need to ship faster.
Universal Problem
Context limits are breaking AI workflows
Developers worldwide are struggling to get the right context for AI tools, without hitting context limits.
Mario Zechner
@badlogic.bsky.social
Cool, then it's not just me holding it wrong. Large context models, like Google's Gemini with a supposed 1-2M context window, are a non-functioning party trick. Aider guy knows what he's doing. In my own work, I found the limit to be 32k tokens, before shit falls apart.
Micky Thompson
@mickythompson
This is a common thought I have when seeing an AI demo: "That's cool, but what's the context window limit?
Bernardo Ferrari
@bernaferrari
I loved @OpenCode_AI but wish the context window with grok were larger, I think the limit is 32k tokens
JoeyZoom
@Joeyzoom_
Limited context window, too many tokens provided. You've hit the... AI Limit. I'll delete my account now
Cartwritte
@dataguru_global
From tokens, in comes the Context Window, which is: how much text an AI can "remember" at once, which is actually in the form of tokens. eg GPT-4 Turbo: 128k tokens (~100 pages). Hit the limit? The AI starts forgetting parts of the chat.
gootecks
@gootecks
It usually comes pre bloated and efforts to de bloat are usually near impossible. Where's the Ai saas that cleans the context window??? 🤷
Mario Zechner
@badlogic.bsky.social
Cool, then it's not just me holding it wrong. Large context models, like Google's Gemini with a supposed 1-2M context window, are a non-functioning party trick. Aider guy knows what he's doing. In my own work, I found the limit to be 32k tokens, before shit falls apart.
Micky Thompson
@mickythompson
This is a common thought I have when seeing an AI demo: "That's cool, but what's the context window limit?
Bernardo Ferrari
@bernaferrari
I loved @OpenCode_AI but wish the context window with grok were larger, I think the limit is 32k tokens
JoeyZoom
@Joeyzoom_
Limited context window, too many tokens provided. You've hit the... AI Limit. I'll delete my account now
Cartwritte
@dataguru_global
From tokens, in comes the Context Window, which is: how much text an AI can "remember" at once, which is actually in the form of tokens. eg GPT-4 Turbo: 128k tokens (~100 pages). Hit the limit? The AI starts forgetting parts of the chat.
gootecks
@gootecks
It usually comes pre bloated and efforts to de bloat are usually near impossible. Where's the Ai saas that cleans the context window??? 🤷
Mario Zechner
@badlogic.bsky.social
Cool, then it's not just me holding it wrong. Large context models, like Google's Gemini with a supposed 1-2M context window, are a non-functioning party trick. Aider guy knows what he's doing. In my own work, I found the limit to be 32k tokens, before shit falls apart.
Micky Thompson
@mickythompson
This is a common thought I have when seeing an AI demo: "That's cool, but what's the context window limit?
Bernardo Ferrari
@bernaferrari
I loved @OpenCode_AI but wish the context window with grok were larger, I think the limit is 32k tokens
JoeyZoom
@Joeyzoom_
Limited context window, too many tokens provided. You've hit the... AI Limit. I'll delete my account now
Cartwritte
@dataguru_global
From tokens, in comes the Context Window, which is: how much text an AI can "remember" at once, which is actually in the form of tokens. eg GPT-4 Turbo: 128k tokens (~100 pages). Hit the limit? The AI starts forgetting parts of the chat.
gootecks
@gootecks
It usually comes pre bloated and efforts to de bloat are usually near impossible. Where's the Ai saas that cleans the context window??? 🤷
Mario Zechner
@badlogic.bsky.social
Cool, then it's not just me holding it wrong. Large context models, like Google's Gemini with a supposed 1-2M context window, are a non-functioning party trick. Aider guy knows what he's doing. In my own work, I found the limit to be 32k tokens, before shit falls apart.
Micky Thompson
@mickythompson
This is a common thought I have when seeing an AI demo: "That's cool, but what's the context window limit?
Bernardo Ferrari
@bernaferrari
I loved @OpenCode_AI but wish the context window with grok were larger, I think the limit is 32k tokens
JoeyZoom
@Joeyzoom_
Limited context window, too many tokens provided. You've hit the... AI Limit. I'll delete my account now
Cartwritte
@dataguru_global
From tokens, in comes the Context Window, which is: how much text an AI can "remember" at once, which is actually in the form of tokens. eg GPT-4 Turbo: 128k tokens (~100 pages). Hit the limit? The AI starts forgetting parts of the chat.
gootecks
@gootecks
It usually comes pre bloated and efforts to de bloat are usually near impossible. Where's the Ai saas that cleans the context window??? 🤷
Zach Tratar
@zachtratar
Although many coding agents can now run for more than 30 minutes, I find that the vast majority of that time is spent on planning and reading random files. The majority of which can be skipped by a better prompt that takes 3 minutes to write.
Adam Galas
@adamgalas.bsky.social
Without continual learning in which the weights of the AI model itself are constantly adapting like the brains of humans as we learn.. The only way around this problem is larger and larger context windows. Theoretically there is no limit to how big a context window could be...
Luke
@luke.creatives
The longer you talk to AI... ...the dumber it gets. That's not a bug. It's context window bloat. It starts summarizing, dropping details, and losing quality the longer you go. You can't just copy the entire chat into a new session either — you'll just recreate the same bloat
Jabol aso
@jabolaso
Instead manually using @ for context, for accuracy, Multiple read file only benefits to vibe coders, real talk. this is bad because ai can read unnecessary or unrelated files and this will only bloat your window context even more faster.
eric zakariasson
@ericzakariasson
do you currently support multiple rule files? we're seeing rules being used for workflows, instructions, boilerplates etc which doesn't make sense to keep in the same file also having dynamic inclusion of rules is important to not bloat the context window when you have them
Peter Butler
@peter-butler.bsky.social
Memories can clog a bot's "context window," or short-term memory, with erroneous or bizarre content. Over a long conversation, this can cause the model to spiral into increasingly untethered outputs. That seems like a big problem!
Zach Tratar
@zachtratar
Although many coding agents can now run for more than 30 minutes, I find that the vast majority of that time is spent on planning and reading random files. The majority of which can be skipped by a better prompt that takes 3 minutes to write.
Adam Galas
@adamgalas.bsky.social
Without continual learning in which the weights of the AI model itself are constantly adapting like the brains of humans as we learn.. The only way around this problem is larger and larger context windows. Theoretically there is no limit to how big a context window could be...
Luke
@luke.creatives
The longer you talk to AI... ...the dumber it gets. That's not a bug. It's context window bloat. It starts summarizing, dropping details, and losing quality the longer you go. You can't just copy the entire chat into a new session either — you'll just recreate the same bloat
Jabol aso
@jabolaso
Instead manually using @ for context, for accuracy, Multiple read file only benefits to vibe coders, real talk. this is bad because ai can read unnecessary or unrelated files and this will only bloat your window context even more faster.
eric zakariasson
@ericzakariasson
do you currently support multiple rule files? we're seeing rules being used for workflows, instructions, boilerplates etc which doesn't make sense to keep in the same file also having dynamic inclusion of rules is important to not bloat the context window when you have them
Peter Butler
@peter-butler.bsky.social
Memories can clog a bot's "context window," or short-term memory, with erroneous or bizarre content. Over a long conversation, this can cause the model to spiral into increasingly untethered outputs. That seems like a big problem!
Zach Tratar
@zachtratar
Although many coding agents can now run for more than 30 minutes, I find that the vast majority of that time is spent on planning and reading random files. The majority of which can be skipped by a better prompt that takes 3 minutes to write.
Adam Galas
@adamgalas.bsky.social
Without continual learning in which the weights of the AI model itself are constantly adapting like the brains of humans as we learn.. The only way around this problem is larger and larger context windows. Theoretically there is no limit to how big a context window could be...
Luke
@luke.creatives
The longer you talk to AI... ...the dumber it gets. That's not a bug. It's context window bloat. It starts summarizing, dropping details, and losing quality the longer you go. You can't just copy the entire chat into a new session either — you'll just recreate the same bloat
Jabol aso
@jabolaso
Instead manually using @ for context, for accuracy, Multiple read file only benefits to vibe coders, real talk. this is bad because ai can read unnecessary or unrelated files and this will only bloat your window context even more faster.
eric zakariasson
@ericzakariasson
do you currently support multiple rule files? we're seeing rules being used for workflows, instructions, boilerplates etc which doesn't make sense to keep in the same file also having dynamic inclusion of rules is important to not bloat the context window when you have them
Peter Butler
@peter-butler.bsky.social
Memories can clog a bot's "context window," or short-term memory, with erroneous or bizarre content. Over a long conversation, this can cause the model to spiral into increasingly untethered outputs. That seems like a big problem!
Zach Tratar
@zachtratar
Although many coding agents can now run for more than 30 minutes, I find that the vast majority of that time is spent on planning and reading random files. The majority of which can be skipped by a better prompt that takes 3 minutes to write.
Adam Galas
@adamgalas.bsky.social
Without continual learning in which the weights of the AI model itself are constantly adapting like the brains of humans as we learn.. The only way around this problem is larger and larger context windows. Theoretically there is no limit to how big a context window could be...
Luke
@luke.creatives
The longer you talk to AI... ...the dumber it gets. That's not a bug. It's context window bloat. It starts summarizing, dropping details, and losing quality the longer you go. You can't just copy the entire chat into a new session either — you'll just recreate the same bloat
Jabol aso
@jabolaso
Instead manually using @ for context, for accuracy, Multiple read file only benefits to vibe coders, real talk. this is bad because ai can read unnecessary or unrelated files and this will only bloat your window context even more faster.
eric zakariasson
@ericzakariasson
do you currently support multiple rule files? we're seeing rules being used for workflows, instructions, boilerplates etc which doesn't make sense to keep in the same file also having dynamic inclusion of rules is important to not bloat the context window when you have them
Peter Butler
@peter-butler.bsky.social
Memories can clog a bot's "context window," or short-term memory, with erroneous or bizarre content. Over a long conversation, this can cause the model to spiral into increasingly untethered outputs. That seems like a big problem!