agenticdisco

agenticdisco

Persistent memory + multi-agent channel for any AI stack.

The official Python SDK for Agentic Disco — the memory layer that never forgets. Drop persistent cross-session memory and multi-agent coordination into any Python app in under 5 minutes.

pip install agenticdisco

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Why

Every LLM conversation resets. Your agents forget everything the moment a session ends. Agentic Disco fixes that with a simple HTTP API — write memory, read it back from any agent, any session, any time.

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Quickstart

from agenticdisco import AgenticDisco

disco = AgenticDisco("your_disco_key")  # Get yours free at agenticdisco.com

# Store a memory
disco.remember("user_goal", "build a web app", category="goals")
disco.remember("preferred_language", "Python", category="preferences")

# Recall all memories
memories = disco.recall()
for m in memories:
    print(f"[{m.category}] {m.key}: {m.value}")

# Recall as a flat dict
context = disco.recall(as_dict=True)
print(context["user_goal"])  # "build a web app"

# Post to the agent channel
disco.post("SCOUT", "Research complete — 12 sources found")
disco.post("FORGE", "Code generated and tested")

# Read the channel
for msg in disco.listen():
    print(f"[{msg.agent_name}] {msg.message}")

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OpenAI Integration — 2 Lines

The most common use case: give your ChatGPT-powered app a persistent memory that survives across sessions.

from openai import OpenAI
from agenticdisco import AgenticDisco

client = OpenAI(api_key="your_openai_key")
disco = AgenticDisco("your_disco_key")

def chat(user_input: str, user_id: str) -> str:
    messages = [{"role": "user", "content": user_input}]

    # ✨ Inject persistent memory — one line
    messages = disco.inject_memory(messages)

    response = client.chat.completions.create(
        model="gpt-4",
        messages=messages
    )

    reply = response.choices[0].message.content

    # ✨ Save the conversation — one line
    messages.append({"role": "assistant", "content": reply})
    disco.save_conversation(messages, agent_name="my-gpt-bot")

    return reply

That's it. Your GPT now remembers user goals, preferences, and past conversations — forever.

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All Methods

Memory

Channel

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Multi-Agent Example

Multiple agents sharing the same memory layer — coordinated via the channel.

from agenticdisco import AgenticDisco

# All agents use the same Disco Key — they share memory automatically
scout  = AgenticDisco("your_disco_key")
forge  = AgenticDisco("your_disco_key")
vera   = AgenticDisco("your_disco_key")

# SCOUT does research, writes findings to memory
scout.remember("research_topic", "persistent memory for AI agents")
scout.remember("sources_found", "12", category="research")
scout.post("SCOUT", "Research complete. 12 sources found.")

# FORGE reads SCOUT's memory and builds on it
context = forge.recall(as_dict=True)
print(context["research_topic"])  # "persistent memory for AI agents"
forge.post("FORGE", f"Building on SCOUT's research: {context['research_topic']}")

# VERA validates and reads the full channel history
for msg in vera.listen():
    print(f"[{msg.agent_name}] {msg.message}")

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Error Handling

from agenticdisco import AgenticDisco, DiscoAuthError, DiscoRateLimitError, DiscoAPIError

disco = AgenticDisco("your_disco_key")

try:
    memories = disco.recall()
except DiscoAuthError:
    print("Invalid Disco Key — get yours at agenticdisco.com")
except DiscoRateLimitError:
    print("Rate limit hit — upgrade at agenticdisco.com/pricing")
except DiscoAPIError as e:
    print(f"API error: {e}")

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Pricing

No credit card required to start. Get your free key →

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Links

• Website: agenticdisco.com
• API Docs: agenticdisco.com/docs
• Get API Key: agenticdisco.com/get-key
• Issues: GitHub Issues

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MIT License © 2026 Agentic Disco