> ## Documentation Index
> Fetch the complete documentation index at: https://docs.screenpipe.com/llms.txt
> Use this file to discover all available pages before exploring further.

# local memory for AI agents

> Give Claude, Codex, Cursor, or another agent useful continuity through small, source-backed local context files.

{/* https://screenpi.pe */}

screenpipe cannot restore an AI model's hidden context. it can give the next session a local record of recent work: what changed, what was decided, what remains open, and where the evidence came from.

## two ways to start

| method                      | choose it when                                                        |
| --------------------------- | --------------------------------------------------------------------- |
| [MCP](/mcp-server) search   | the agent should query recent screen history on demand                |
| periodic local context file | several tools need the same compact project state over days or months |

```mermaid theme={null}
flowchart TD
    A["bounded screenpipe history"] --> B["extract facts and open loops"]
    B --> C["reviewed local context file"]
    C --> D["Claude, Codex, Cursor, or another agent"]
    D --> E["new work"]
    E --> A
```

## build a context file

<Steps>
  <Step title="choose one destination">
    Start with one Markdown file in a private project folder, wiki, or Obsidian vault. avoid creating several competing memory stores on day one.
  </Step>

  <Step title="define the schema">
    Keep current objectives, recent changes, decisions, open loops, blockers, and source time ranges. separate durable facts from short-lived activity.
  </Step>

  <Step title="generate it manually">
    Ask screenpipe or your MCP-connected agent to review a bounded period and update the file. require it to preserve still-valid entries and mark missing evidence.
  </Step>

  <Step title="review the first updates">
    Remove secrets and irrelevant personal detail. confirm that decisions were accepted rather than merely discussed.
  </Step>

  <Step title="teach agents how to use it">
    Add one line to the project's agent instructions telling tools to read the file at the start of relevant work and update it only under your chosen policy.
  </Step>

  <Step title="schedule only after it is stable">
    Once manual updates are reliable, run the pipe hourly or daily. keep a last-updated time and an explicit “no new evidence” state.
  </Step>
</Steps>

## starter schema

```markdown theme={null}
# project context

last reviewed: <timestamp>
source window: <start> to <end>

## current objective
- ...

## recent verified changes
- fact — source: <app or meeting>, <time range>

## decisions
- accepted decision — owner — date

## open loops
- action — owner if known — status — source

## blockers and unknowns
- ...

## sensitive details intentionally omitted
- ...
```

## update prompt

```markdown theme={null}
Update the local project context from this bounded screenpipe history.
Preserve still-valid facts from the existing file.
Add only facts supported by the supplied results.
Distinguish decisions from proposals and completed work from viewed work.
Keep source app or meeting and time range for each material change.
If the source is missing, record an unknown instead of guessing.
Never store secrets, tokens, raw private conversations, or unrelated personal data.
```

<Warning>
  a memory file concentrates context. keep it local or in an access-controlled repository, exclude secrets, and define retention before scheduling recurring updates.
</Warning>