Sessions forget
1Agents drop architecture, conventions, and context the moment a session times out. You rewrite history every time.
Memory that ships code
Built for high performance teamsThe memory layer that makes AI feel senior
Codemory gives teams a living, permissioned memory graph that your IDE copilots, chat agents, and internal tools all share. Work continues from context, not from scratch.
What teams feel with Codemory
Share architecture once and let every assistant stay fluent in your stack.
Shared memoryLive
Episodes
01Conversations, commits, PRs, incidents, and decisions stay linked with provenance and time.
Entities
02Services, endpoints, libraries, teams, and environments join the same living memory graph.
Relationships
03See what depends on what, which decision changed which module, and why tradeoffs were made.
Trusted by teams who refuse to start from zero
From launches to critical production support, Codemory powers the memory layer that keeps agents, copilots, and reviewers aligned.
Product teams
Launch new assistants with the same house style, helper functions, and decisions codified into Codemory.
Support orgs
Reopen conversations midstream. CSAT lifts when every reply remembers the last one.
Platform leads
Govern memory, observe recall rates, and ship compliance ready copilots without slowing velocity.
The problem (you've felt it)
Repeating your codebase to every LLM is the hidden tax slowing your team
Without a shared, living memory layer, every new session starts from zero. Context is fragmented, onboarding drags, and even the best models feel junior.
The Result
Costly rework, slow reviews, and AI that never feels senior, no matter how powerful the model.
Codemory was designed to eliminate this tax by orchestrating context across every tool, making your entire stack context aware.
Markdown memory files don't scale
2Static docs drift out of date, eat tokens, and flatten relationships that your teams and copilots need to understand decisions.
Tool silos multiply work
3Claude knows one thing, ChatGPT another, Cursor a third. None of them share context, so your developers copy and paste glue.
Tribal knowledge disappears
4Debug histories, design decisions, and team conventions leave with the person who remembered them, not the org that needs them.
These problems compound over time. What starts as minor friction becomes a massive drag on velocity, quality, and team morale.
The Codemory answer
A living memory graph for your code, teams, and tools
Codemory replaces static files and ad hoc prompts with a permissioned, version aware graph that evolves with your repos and workflows. Every tool and teammate taps into the same living source of truth.
Episodes
Entities
Relationships
Retrieval
1
Episodes
Codemory records conversations, commits, pull requests, incidents, and decisions with provenance and time so every moment has context.
→ Replay design debates or incident timelines verbatim when a teammate or agent needs to understand what happened and why.
2
Entities
Services, endpoints, libraries, people, teams, and environments stay linked in a single, permissioned graph.
→ See which helper lives where, who owns it, and which versions are safe to call across repos and regions.
3
Relationships
Codemory captures the dependencies between modules, the trade-offs behind changes, and the impact of each decision.
→ Trace why an architectural bet was made, which PR implemented it, and how downstream services rely on it.
4
Selective retrieval
Only the relevant slice of memory is delivered to each task. Database threads answer DB questions, style rules guide CSS, and incident knowledge supports on call.
→ Stop dumping 2,000-word prompts. Codemory feeds every tool exactly what it needs and nothing more.
The result: copilots ideate in ChatGPT, implement in Claude Code, and review in Cursor without losing the plot. Codemory keeps the thread unbroken across every LLM, repo, and release.
What you can do with Codemory
Give every tool, teammate, and agent the same version aware context
From copilots that cite helper functions to on-call retros that relive the exact fix, Codemory unlocks durable memory across the software lifecycle.
Project aware coding copilot
Your copilot remembers file structure, naming patterns, API contracts, environment conventions, and review rules for every repo.
Example: "In the auth service, tokens are RS256; use verifyTenant() from utils/security.ts."
Multi repository, version locked memory
Keep one memory layer across services with per repo version documentation and changelog awareness.
Example: "Service A is on FastAPI 0.110; use the pydantic v2 pattern here."
Debugging & incident recall
Codify recurring errors, root causes, and exact fixes linked to pull requests, tickets, and runbooks.
Example: "This KeyError was fixed in PR #482 by adding Field(alias=...) to UserModel."
Shared team conventions
Store org wide coding conventions, architecture decisions, security rules, and how you review.
Example: "Never use requests; standardize on httpx with retry policy X."
Developer journal & knowledge base
Record every decision, tradeoff, and experiment with provenance and timestamps for compliance and continuity.
Example: "Why did we switch MongoDB → Postgres in Q3 2024? See decision thread and benchmarks."
Cross tool dev memory
Maintain one memory across ChatGPT, Claude, Cursor, VS Code, and every MCP capable surface.
Example: Continue an investigation in Cursor using the same Codemory context you started in ChatGPT.
Outcomes you can measure
Codemory turns shared memory into undeniable productivity wins
Track recall latency, hit rates, and downstream wins inside the Codemory console. Show the math on rework saved, incidents prevented, and onboarding accelerated.
30 min
Time saved per engineer
Codemory keeps copilots on context so devs skip the re explanation ritual every morning.
12 pts
Lift in CSAT
Support agents reopen Codemory timelines and resolve follow ups without restarting the story.
3×
Faster PR approvals
Reviews ship quickly when suggestions match the exact house style, helper functions, and versions.
How Codemory works in three steps
Connect, ingest, and retrieve. Everything stays observable, permission aware, and programmable. The memory layer evolves as fast as your code.
01
Connect
Minutes, not monthsLink GitHub, Linear or Jira, Slack, Confluence, and IDE agents via MCP in minutes with no workflow rewrites required.
02
Ingest & structure
Continuous syncCodemory auto extracts episodes, entities, and relationships, dedupes, version locks, and tracks changelogs across repos.
03
Retrieve & apply
<50ms recallWhen you ask for help, Codemory feeds only the relevant, permission filtered memory to the model and learns from the outcome.
Access Codemory your way
API, MCP server, or native SDKs
Use Codemory with any LLM provider through our Model Context Protocol server, integrate directly via REST API, or leverage type safe SDKs.
Code first
Native SDKs
TypeScript and Python SDKs for direct integration into your workflows and applications.
Universal
MCP Server
Model Context Protocol server compatible with any LLM provider including Claude, GPT, Gemini, and more.
Flexible
REST API
Full featured HTTP API for custom integrations and platform specific implementations.
Codemory SDKs
Pair Codemory with any LLM using TypeScript & Python building blocks
Install the Codemory SDKs in the stack you already have. Persist context, orchestrate memory graphs, and replay timelines with just a few lines of code.
Use the quickstart cards below to explore common Codemory recipes:
- Bootstrap memory timelines across frontend agents and browsers.
- Maintain context across Python research copilots and workflows.
- Link Codemory across planners, executors, and human reviewers.
Codemory TypeScript SDKCopy & paste ready
import { Codemory } from '@codemory/sdk';
const apiKey = process.env.CODEMORY_API_KEY;
if (!apiKey) {
throw new Error('Missing CODEMORY_API_KEY environment variable');
}
const codemory = new Codemory({
apiKey,
baseUrl: process.env.CODEMORY_API_BASE ?? 'https://api.codemory.com',
timeout: 10_000,
});
type MemoryFabricConfig = {
orgId: string;
repos: string[];
linearTeams: string[];
slackChannels: string[];
knowledgeSpaces: string[];
};
export async function bootstrapMemoryFabric(config: MemoryFabricConfig) {
const runtime = await codemory.runtime.activate({
orgId: config.orgId,
surfaces: [
{
connector: 'github',
repos: config.repos,
captureReviews: true,
syncDeploys: true,
},
{
connector: 'linear',
teamIds: config.linearTeams,
includeComments: true,
trackIncidents: true,
},
{
connector: 'slack',
channels: config.slackChannels,
captureThreads: true,
escalateEmoji: ':codemory:',
},
{
connector: 'confluence',
spaces: config.knowledgeSpaces,
followUpdates: true,
},
{
connector: 'mcp',
tools: ['cursor', 'chatgpt', 'claude'],
autoProvision: true,
},
],
watchers: [
{
name: 'release-moments',
triggers: [
{ connector: 'github', event: 'pull_request.merged' },
{ connector: 'linear', event: 'issue.closed' },
],
memoryTemplate: 'release-brief',
relationships: [
{
from: { connector: 'github', field: 'pull_request.id' },
to: { connector: 'linear', field: 'issue.id' },
type: 'resolves',
},
{
from: { connector: 'github', field: 'pull_request.id' },
to: { connector: 'confluence', field: 'page.id' },
type: 'documents',
},
],
},
{
name: 'incident-timelines',
triggers: [
{
connector: 'slack',
event: 'message.tagged',
filter: { emoji: ':incident:' },
},
],
memoryTemplate: 'incident-timeline',
captureTranscripts: true,
},
{
name: 'customer-loops',
triggers: [{ connector: 'linear', event: 'ticket.reopened' }],
memoryTemplate: 'customer-history',
followUps: { window: '30d' },
},
],
});
await codemory.context.templates.upsert({
orgId: config.orgId,
templates: [
{
name: 'ship-brief',
include: {
memories: { tags: ['release'], window: '60d', max: 15 },
graph: { hops: 2, includeIncidents: true },
transcripts: true,
},
},
{
name: 'incident-review',
include: {
memories: { tags: ['incident'], window: '120d', max: 10 },
graph: { hops: 3, includeIncidents: true },
attachments: true,
},
},
{
name: 'customer-history',
include: {
memories: { tags: ['support'], window: '180d', max: 20 },
graph: { hops: 1 },
conversations: true,
},
},
],
});
return runtime;
}
import { Codemory } from '@codemory/sdk';
const apiKey = process.env.CODEMORY_API_KEY;
if (!apiKey) {
throw new Error('Missing CODEMORY_API_KEY environment variable');
}
const codemory = new Codemory({
apiKey,
baseUrl: process.env.CODEMORY_API_BASE ?? 'https://api.codemory.com',
timeout: 10_000,
});
type MemoryFabricConfig = {
orgId: string;
repos: string[];
linearTeams: string[];
slackChannels: string[];
knowledgeSpaces: string[];
};
export async function bootstrapMemoryFabric(config: MemoryFabricConfig) {
const runtime = await codemory.runtime.activate({
orgId: config.orgId,
surfaces: [
{
connector: 'github',
repos: config.repos,
captureReviews: true,
syncDeploys: true,
},
{
connector: 'linear',
teamIds: config.linearTeams,
includeComments: true,
trackIncidents: true,
},
{
connector: 'slack',
channels: config.slackChannels,
captureThreads: true,
escalateEmoji: ':codemory:',
},
{
connector: 'confluence',
spaces: config.knowledgeSpaces,
followUpdates: true,
},
{
connector: 'mcp',
tools: ['cursor', 'chatgpt', 'claude'],
autoProvision: true,
},
],
watchers: [
{
name: 'release-moments',
triggers: [
{ connector: 'github', event: 'pull_request.merged' },
{ connector: 'linear', event: 'issue.closed' },
],
memoryTemplate: 'release-brief',
relationships: [
{
from: { connector: 'github', field: 'pull_request.id' },
to: { connector: 'linear', field: 'issue.id' },
type: 'resolves',
},
{
from: { connector: 'github', field: 'pull_request.id' },
to: { connector: 'confluence', field: 'page.id' },
type: 'documents',
},
],
},
{
name: 'incident-timelines',
triggers: [
{
connector: 'slack',
event: 'message.tagged',
filter: { emoji: ':incident:' },
},
],
memoryTemplate: 'incident-timeline',
captureTranscripts: true,
},
{
name: 'customer-loops',
triggers: [{ connector: 'linear', event: 'ticket.reopened' }],
memoryTemplate: 'customer-history',
followUps: { window: '30d' },
},
],
});
await codemory.context.templates.upsert({
orgId: config.orgId,
templates: [
{
name: 'ship-brief',
include: {
memories: { tags: ['release'], window: '60d', max: 15 },
graph: { hops: 2, includeIncidents: true },
transcripts: true,
},
},
{
name: 'incident-review',
include: {
memories: { tags: ['incident'], window: '120d', max: 10 },
graph: { hops: 3, includeIncidents: true },
attachments: true,
},
},
{
name: 'customer-history',
include: {
memories: { tags: ['support'], window: '180d', max: 20 },
graph: { hops: 1 },
conversations: true,
},
},
],
});
return runtime;
}
✔ Checking project structure. Found Next.js/TypeScript.✔ Validating git repository.✔ Configuring .codemoryignore.✔ Initializing memory graph.✔ Connecting to Codemory API.✔ Writing codemory.config.json.✔ Installing Codemory SDK.ℹ Updated 1 file:- lib/codemory.tsWhy Codemory wins vs memory files
Context that evolves as fast as your code, governed for enterprise scale
Static markdown cannot keep pace. Codemory automatically ingests, version locks, and governs memory so every LLM, teammate, and tool starts from the same trusted truth while satisfying the most rigorous security reviews.
Core capabilities
Built for teams who need context that actually works
Automatically ingested, version aware context
Codemory listens to your repos, tickets, and docs to keep memory current with no manual markdown upkeep or stale facts.
Selective task aware retrieval
Only the relevant slice of context is streamed into prompts, protecting tokens and latency without sacrificing depth.
Graph relationships & provenance
Understand what depends on what, why tradeoffs were made, and who approved the change with temporal history built in.
Cross tool continuity
Start in ChatGPT, continue in Claude, review in Cursor. Codemory keeps every LLM and IDE on the same thread via MCP connectors.
Enterprise-grade governance
Security, privacy, and control without slowing momentum
Security & compliance
SSO and SAML, RBAC and ABAC, per repo and per team scoping, audit logs, retention controls, and encryption in transit and at rest.
Learn more
Privacy & governance
Least privilege connectors, redaction rules, PII filters, and right to forget APIs keep sensitive data in bounds.
Learn more
Deployment options
Run Codemory in our cloud or self host in your VPC with regional data residency for regulated environments.
Learn more
Observability
Usage analytics, memory hit rates, retrieval visibility, and policy simulation ensure you see exactly how context flows.
Learn more
Shared, permissioned memory
Role scoped access, redaction rules, and least privilege connectors ensure each team sees exactly what they should.
Learn more
Admin controls
Org level policies, memory rules, and approval workflows give platform teams confident guardrails.
Learn more
Ready for procurement? Request our security brief, SOC2 report, or DPA to accelerate vendor review.
What teams are saying
Real results from engineering teams using Codemory
From faster code reviews to eliminated context switching, teams report measurable improvements when every tool shares the same memory.
SM
Engineering Lead
Code reviews went from three days to same day approvals. Copilots remember our conventions and API patterns across every session.
MC
VP Engineering
New engineers ramp in days instead of weeks. They inherit decision history and team conventions automatically.
AT
CTO
Version locked memory means LLMs never guess which API version to use. Debugging incidents is instant with full context.
SM
Engineering Lead
Code reviews went from three days to same day approvals. Copilots remember our conventions and API patterns across every session.
MC
VP Engineering
New engineers ramp in days instead of weeks. They inherit decision history and team conventions automatically.
AT
CTO
Version locked memory means LLMs never guess which API version to use. Debugging incidents is instant with full context.
SM
Engineering Lead
Code reviews went from three days to same day approvals. Copilots remember our conventions and API patterns across every session.
MC
VP Engineering
New engineers ramp in days instead of weeks. They inherit decision history and team conventions automatically.
AT
CTO
Version locked memory means LLMs never guess which API version to use. Debugging incidents is instant with full context.
SM
Engineering Lead
Code reviews went from three days to same day approvals. Copilots remember our conventions and API patterns across every session.
MC
VP Engineering
New engineers ramp in days instead of weeks. They inherit decision history and team conventions automatically.
AT
CTO
Version locked memory means LLMs never guess which API version to use. Debugging incidents is instant with full context.
JL
Senior Developer
Context flows seamlessly between ChatGPT, Claude, and Cursor. No more copy and pasting history between tools.
PP
DevOps Manager
MTTR dropped 40%. On call engineers see the complete incident timeline with original error, fix PR, and postmortem linked.
CA
Product Engineering
Graph relationships track why decisions were made and dependencies. Tribal knowledge became institutional knowledge.
JL
Senior Developer
Context flows seamlessly between ChatGPT, Claude, and Cursor. No more copy and pasting history between tools.
PP
DevOps Manager
MTTR dropped 40%. On call engineers see the complete incident timeline with original error, fix PR, and postmortem linked.
CA
Product Engineering
Graph relationships track why decisions were made and dependencies. Tribal knowledge became institutional knowledge.
JL
Senior Developer
Context flows seamlessly between ChatGPT, Claude, and Cursor. No more copy and pasting history between tools.
PP
DevOps Manager
MTTR dropped 40%. On call engineers see the complete incident timeline with original error, fix PR, and postmortem linked.
CA
Product Engineering
Graph relationships track why decisions were made and dependencies. Tribal knowledge became institutional knowledge.
JL
Senior Developer
Context flows seamlessly between ChatGPT, Claude, and Cursor. No more copy and pasting history between tools.
PP
DevOps Manager
MTTR dropped 40%. On call engineers see the complete incident timeline with original error, fix PR, and postmortem linked.
CA
Product Engineering
Graph relationships track why decisions were made and dependencies. Tribal knowledge became institutional knowledge.
Join hundreds of engineering teams who've eliminated context loss and accelerated their development velocity with Codemory.
Pricing for every memory footprint.
Every tier includes SDKs, APIs, and observability. Start free, scale with usage based limits, or secure a dedicated deployment tailored to your governance needs.
Start Free
Test Codemory on side projects, sandboxes, and proof of concept copilots.
Up to 3 apps & namespaces
25k memory events stored
Selective recall APIs
TypeScript & Python SDKs
Community & docs support
Popular
Scale
Roll Codemory out across teams building production copilots and automations.
Unlimited apps, namespaces & teammates
500k memory events per month
Memory graph API & streaming recall
Version locked changelog ingestion
RBAC with audit trails
Priority Slack support
Enterprise
Dedicated infrastructure, deployments, and controls for regulated organisations.Custom.
Self hosted or VPC deployment
Millions of memory events with SLO backed recall
SOC2, ISO27001 & custom security reviews
SAML, SCIM & granular governance
Data residency & redaction policies
White glove onboarding & training
Dedicated solutions architect
Start building with persistent memory
Join engineering teams who've eliminated context loss. Get early access to Codemory and make every LLM, copilot, and teammate share the same version aware memory layer.
Free tier available. No credit card required.