Abigail/minor fix (#351)
* fix: updating vibecoding * fix: brooken links
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ajspig
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@ -10,7 +10,7 @@ Advanced features give you fine-grained control over Honcho's behavior and imple
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## Configuration & Monitoring
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- [Queue Status](/v3/documentation/features/advanced/queue-status) - Monitor background processing and reasoning tasks
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- [Configuration](/v3/documentation/features/advanced/toggle-reasoning) - Configure reasoning models and behavior
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- [Configuration](/v3/documentation/features/advanced/reasoning-configuration) - Configure reasoning models and behavior
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- [Summarizer](/v3/documentation/features/advanced/summarizer) - Automatic session summarization
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## Querying & Filtering
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@ -1,7 +1,7 @@
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---
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title: "AI-Powered Honcho Setup"
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icon: "wand-magic-sparkles"
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description: "Universal starter prompt and Claude Code skill for building with Honcho"
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description: "Agent skills and starter prompt for building with Honcho"
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sidebarTitle: 'Vibecoding Setup'
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---
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@ -14,38 +14,44 @@ We follow the llms.txt standard. There are both an llms.txt and llms-full.txt av
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---
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## Claude Code Skill
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## Agent Skills
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If you're using [Claude Code](https://docs.anthropic.com/en/docs/claude-code/overview), you can install the Honcho integration skill for a guided, interactive setup experience. The skill will explore your codebase, ask targeted questions about your integration needs, and implement Honcho step by step.
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### Installation
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We provide agent skills for coding assistants like Claude Code, Cursor, Windsurf, and others.
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<CodeGroup>
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```bash Global Installation (all projects)
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# Add to your global skills directory
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curl -o ~/.claude/skills/honcho-integration.md https://raw.githubusercontent.com/plastic-labs/honcho/main/docs/SKILL.md
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```bash Install via npx (Recommended)
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npx skills add plastic-labs/honcho
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```
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```bash Project-specific Installation
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# Add to your project's .claude directory
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mkdir -p .claude/skills
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curl -o .claude/skills/honcho-integration.md https://raw.githubusercontent.com/plastic-labs/honcho/main/docs/SKILL.md
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```bash Install as Claude Skill Manually
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curl -o ~/.claude/skills/honcho-integration.md https://raw.githubusercontent.com/plastic-labs/honcho/main/docs/SKILL.md
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```
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</CodeGroup>
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### Usage
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### Available Skills
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Once installed, invoke the skill in Claude Code:
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#### honcho-integration
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```
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/honcho-integration
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```
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**For new integrations.** This skill helps you add Honcho to an existing Python or TypeScript codebase. It provides a guided, interactive experience:
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The skill will:
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1. **Explore your codebase** to understand your language, framework, and existing AI/LLM integrations
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2. **Interview you** about which entities should be peers, your preferred integration pattern, and session structure
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3. **Implement the integration** based on your answers
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4. **Verify the setup** to ensure everything is configured correctly
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1. **Explores your codebase** to understand your language, framework, and existing AI/LLM integrations
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2. **Interviews you** about which entities should be peers, your preferred integration pattern, and session structure
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3. **Implements the integration** based on your answers—installing the SDK, creating peers, configuring sessions, and wiring up the chat endpoint
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4. **Verifies the setup** to ensure everything is configured correctly
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Invoke with `/honcho-integration` in your coding agent.
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#### migrate-honcho-py / migrate-honcho-ts
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**For SDK upgrades.** Migrates code from v1.6.0 to v2.0.0 (required for Honcho 3.0.0). Use when upgrading the SDK or seeing errors about removed APIs like `observations`, `Representation`, `.core`, or `get_config`.
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Both skills handle: terminology changes (`Observation` → `Conclusion`), `Representation` class removal, method renames, and streaming API updates.
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| Python | TypeScript |
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|--------|------------|
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| `/migrate-honcho-py` | `/migrate-honcho-ts` |
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| `AsyncHoncho` → `.aio` accessor | `@honcho-ai/core` removal |
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| | `snake_case` → `camelCase` |
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---
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@ -879,7 +879,7 @@ If `created_at` is not provided, messages will use the server's current timestam
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### Metadata and Filtering
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See [Using Filters](/v3/guides/using-filters) for more examples on how to use filters.
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See [Using Filters](/v3/documentation/features/advanced/using-filters) for more examples on how to use filters.
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<CodeGroup>
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```python Python
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@ -237,7 +237,7 @@ and Bob. We:
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As soon as you save a message in Honcho, it will start to reason about it to
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pull out insights and develop a profile of the user. This is the default
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behavior and can be toggled off via [the configuration](/v3/documentation/core-concepts/configuration).
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behavior and can be toggled off via [the configuration](/v3/documentation/features/advanced/reasoning-configuration).
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## Next Steps
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@ -53,7 +53,7 @@ This feature is illustrated in the graphic below:
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We can enable local representation for a `Peer` by setting `observe_others=True`.
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This is shown in the [Configure
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Reasoning](/v3/documentation/core-concepts/configuration) page.
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Reasoning](/v3/documentation/features/advanced/reasoning-configuration) page.
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Now if we used Bob's local representation of Alice then Bob would only get
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insights on what they've seen Alice say to them.
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@ -97,7 +97,7 @@ results = storage.search("query", filters={
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})
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```
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For the full filter syntax including logical operators (AND, OR, NOT), comparison operators, and metadata filtering, see the [Using Filters](https://docs.honcho.dev/v3/documentation/core-concepts/features/using-filters) documentation.
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For the full filter syntax including logical operators (AND, OR, NOT), comparison operators, and metadata filtering, see the [Using Filters](https://docs.honcho.dev/v3/documentation/features/advanced/using-filters) documentation.
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<Note>
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For comprehensive details about CrewAI's memory system, see the [official CrewAI Memory documentation](https://docs.crewai.com/en/concepts/memory).
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@ -282,13 +282,13 @@ Now that you have a working CrewAI integration with Honcho, you can:
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<Card title="Honcho Architecture" icon="sitemap" href="/v3/documentation/core-concepts/architecture">
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Understand Honcho's peer-based model and core primitives
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</Card>
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<Card title="Get Context" icon="messages" href="/v3/documentation/core-concepts/features/get-context">
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<Card title="Get Context" icon="messages" href="/v3/documentation/features/get-context">
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Learn about retrieving and formatting conversation context
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</Card>
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<Card title="Dialectic API" icon="brain" href="/v3/documentation/core-concepts/features/dialectic">
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<Card title="Chat API" icon="brain" href="/v3/documentation/features/chat">
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Query `peer` representations for deeper understanding
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</Card>
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<Card title="LangGraph Integration" icon="diagram-project" href="/v3/integrations/langgraph">
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<Card title="LangGraph Integration" icon="diagram-project" href="/v3/guides/integrations/langgraph">
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Build stateful agents with LangGraph and Honcho
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</Card>
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</CardGroup>
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@ -227,7 +227,7 @@ const graph = new StateGraph(StateAnnotation)
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### Understanding get_context()
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The [`get_context()`](/v3/documentation/core-concepts/features/get-context) method retrieves comprehensive conversation context and formats it for your LLM. It automatically:
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The [`get_context()`](/v3/documentation/features/get-context) method retrieves comprehensive conversation context and formats it for your LLM. It automatically:
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- **Manages conversation history** - Tracks all messages and determines what's relevant
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- **Respects token limits** - Stays within context window constraints without manual counting
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@ -248,7 +248,7 @@ That's it. Call `session.get_context().to_openai(assistant)` and you get properl
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</Tip>
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<Note>
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For more details on all available parameters, see [`get_context() documentation`](/v3/documentation/core-concepts/features/get-context)
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For more details on all available parameters, see [`get_context() documentation`](/v3/documentation/features/get-context)
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</Note>
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## Chat Loop
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@ -354,10 +354,10 @@ Now that you have a working LangGraph integration with Honcho, you can:
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## Related Resources
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<CardGroup cols={2}>
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<Card title="Get Context" icon="messages" href="/v3/documentation/core-concepts/features/get-context">
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<Card title="Get Context" icon="messages" href="/v3/documentation/features/get-context">
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Learn more about retrieving and formatting conversation context
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</Card>
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<Card title="MCP Integration" icon="star-of-life" href="/v3/integrations/mcp">
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<Card title="MCP Integration" icon="star-of-life" href="/v3/guides/integrations/mcp">
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Use Honcho in Claude Desktop with MCP
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</Card>
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</CardGroup>
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@ -259,14 +259,14 @@ Reference the [API Comparison](#api-comparison) to replace your Mem0 API calls w
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Mem0 requires manual assembly of context from `search()` results. Honcho's `session.get_context()` returns a ready-to-use `SessionContext` object with built-in token limits, auto-included summaries, and format helpers (`.to_openai()`, `.to_anthropic()`).
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<Card title="Get Context" icon="window-restore" href="../../documentation/core-concepts/features/get-context">
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<Card title="Get Context" icon="window-restore" href="../../documentation/features/get-context">
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Learn more about token-optimized context retrieval
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</Card>
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Mem0's `search()` returns basic vector, semantic, or raw memory matches. Honcho's `peer.chat()` enables your agent to *reason* about what it knows—returning synthesized natural language insights with streaming support and scoped queries.
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<Card title="Dialectic Endpoint" icon="brain" href="../../documentation/core-concepts/features/dialectic-endpoint">
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<Card title="Chat Endpoint" icon="brain" href="../../documentation/features/chat">
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Learn more about inference-powered queries
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</Card>
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@ -285,7 +285,7 @@ Additional features with **no Mem0 equivalent**:
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<Card title="Architecture" icon="rocket" href="../../documentation/core-concepts/architecture">
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Understand peers and sessions
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</Card>
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<Card title="Dialectic API" icon="brain" href="../../documentation/core-concepts/features/dialectic-endpoint">
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<Card title="Chat API" icon="brain" href="../../documentation/features/chat">
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Inference responses
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</Card>
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<Card title="Guides" icon="book" href="../../guides/overview">
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@ -16,10 +16,10 @@ Each guide focuses on a specific use case with practical examples. The goal is t
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Quick integration guides to get up and running:
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<CardGroup cols={2}>
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<Card title="MCP Integration" icon="link" href="/v3/integrations/mcp">
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<Card title="MCP Integration" icon="link" href="/v3/guides/integrations/mcp">
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Get Honcho running with a single prompt in Claude Code
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</Card>
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<Card title="LangGraph" icon="diagram-project" href="/v3/integrations/langgraph">
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<Card title="LangGraph" icon="diagram-project" href="/v3/guides/integrations/langgraph">
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Add persistent memory and theory of mind to your LangGraph agents
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</Card>
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</CardGroup>
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@ -42,7 +42,7 @@ Once a `Message` is saved in Honcho, it will kick off a background task that
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looks at the new data to generate insights about the `Peer` that sent the `Message`
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This is the default behavior of Honcho and can be turned off by [configuring the
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Peer or Session](/v3/documentation/core-concepts/configuration)
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Peer or Session](/v3/documentation/features/advanced/reasoning-configuration)
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This pattern of having a Peer, Session, and Messages is highly flexible and
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works for many different use cases and agent setups. Some use cases may only
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@ -259,14 +259,14 @@ Reference the [API Comparison](#api-comparison) to replace your Mem0 API calls w
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Mem0 requires manual assembly of context from `search()` results. Honcho's `session.get_context()` returns a ready-to-use `SessionContext` object with built-in token limits, auto-included summaries, and format helpers (`.to_openai()`, `.to_anthropic()`).
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<Card title="Get Context" icon="window-restore" href="../../documentation/core-concepts/features/get-context">
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<Card title="Get Context" icon="window-restore" href="../../documentation/features/get-context">
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Learn more about token-optimized context retrieval
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</Card>
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Mem0's `search()` returns basic vector, semantic, or raw memory matches. Honcho's `peer.chat()` enables your agent to *reason* about what it knows—returning synthesized natural language insights with streaming support and scoped queries.
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<Card title="Dialectic Endpoint" icon="brain" href="../../documentation/core-concepts/features/dialectic-endpoint">
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<Card title="Chat Endpoint" icon="brain" href="../../documentation/features/chat">
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Learn more about inference-powered queries
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</Card>
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@ -285,7 +285,7 @@ Additional features with **no Mem0 equivalent**:
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<Card title="Architecture" icon="rocket" href="../../documentation/core-concepts/architecture">
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Understand peers and sessions
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</Card>
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<Card title="Dialectic API" icon="brain" href="../../documentation/core-concepts/features/dialectic-endpoint">
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<Card title="Chat API" icon="brain" href="../../documentation/features/chat">
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Inference responses
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</Card>
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<Card title="Guides" icon="book" href="../../guides/overview">
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