Snipara Agents

Build AI agents that remember, share context, and coordinate. Snipara Agents provides the infrastructure layer for production agent workflows.

Standalone Product

Snipara Agents complements Snipara Context. You can use either or both together for comprehensive agent infrastructure.

The Problem

AI agents today are stateless. Every conversation starts fresh. Past decisions, user preferences, learned patterns — all gone. This creates several challenges:

No memory persistence — Agents forget everything between sessions
No knowledge sharing — One agent's discovery stays siloed
No coordination — Multiple agents can't work together effectively
Repeated context loading — Same docs fetched over and over

The Solution

Snipara Agents provides four core capabilities delivered via MCP (Model Context Protocol):

🧠

Agent Memory

Persistent semantic memory for individual agents. Store facts, decisions, and preferences with confidence decay.

👥

Group Memory

Shared memory across agents and teammates. One agent's discovery becomes available to all.

🔗

Multi-Agent Coordination

Real-time state sync, resource locking, and task handoffs. Build swarms that coordinate.

🤖

Autonomous Agent Runtime

Observe-think-act loops with sandboxed code execution, sub-LLM orchestration, and trajectory logging.

How It Works

Snipara Agents exposes MCP tools that your LLM can call to store, retrieve, and share memory. The LLM decides when to remember something important and when to recall relevant context.

// Agent remembers a user preference

rlm_remember({

  content: "User prefers TypeScript over JavaScript",

  type: "preference",

  confidence: 0.9

})

// Later, agent recalls relevant memories

rlm_recall({

  query: "What programming language does the user prefer?",

  limit: 5

})

Quick Start

Subscribe to Agents

Get API Key

Add MCP Config

Start Building

1. Subscribe to Snipara Agents

Go to your Billing page and subscribe to a Snipara Agents plan. Plans start at $15/month.

2. Get Your API Key

Navigate to your project's API Keys tab and create a new key. This key will be used to authenticate MCP requests.

3. Add MCP Configuration

Add Snipara Agents to your MCP client configuration:

  "mcpServers": {

    "snipara-agents": {

      "type": "http",

      "url": "https://api.snipara.com/mcp/YOUR_PROJECT_SLUG",

      "headers": {

        "X-API-Key": "YOUR_API_KEY"

4. Start Using Agent Tools

Once configured, your LLM will have access to memory and coordination tools. Ask it to "remember this for next time" or "recall what we discussed about authentication".

MCP Tools

Tool	Description	Plan
`rlm_remember`	Store a memory with type, category, and TTL	Starter+
`rlm_recall`	Semantic recall of relevant memories	Starter+
`rlm_memories`	List memories with filters	Starter+
`rlm_forget`	Delete specific memories	Starter+
`rlm_swarm_create`	Create a new agent swarm	Starter+
`rlm_swarm_join`	Join an existing swarm	Starter+
`rlm_claim`	Claim exclusive access to a resource	Pro+
`rlm_release`	Release a resource claim	Pro+
`rlm_state_get/set`	Read/write shared swarm state	Pro+
`rlm_broadcast`	Send event to other agents	Team+
`rlm_task_create`	Create a task in the queue	Pro+
`rlm_task_claim`	Claim a task from the queue	Pro+
`rlm_task_complete`	Mark a task as complete	Pro+

Pricing

Plan	Price	Memories	Retention	Swarms
Starter	$15/mo	1,000	7 days	1 (2 agents)
Pro	$39/mo	5,000	30 days	5 (5 agents each)
Team	$79/mo	25,000	90 days	20 (15 agents each)
Enterprise	$199/mo	Unlimited	Unlimited	Unlimited (50 agents)

Next Steps

Agent Memory

Learn how to store and recall memories for individual agents.

Group Memory

Share knowledge across multiple agents and team members.

Multi-Agent Coordination

Build agent swarms with resource locking and task queues.

Go to Dashboard

Start building with Snipara Agents now.