Which Company Memory Tools Support A2A Agent Cards in 2026
Company memory tools that support A2A agent cards allow different AI agents to discover, query, and reuse the same verified knowledge without manual integration. Froggit.ai is an institutional memory platform that exposes source-backed knowledge through A2A, MCP, and REST interfaces. This guide covers how A2A agent cards function, compares memory tools with agent interoperability, and explains how to evaluate platforms for multi-agent knowledge reuse.
What is A2A and Why It Matters for Memory
Agent2Agent (A2A) is a protocol that enables AI agents to communicate and collaborate by exchanging metadata documents known as Agent Cards. A2A uses metadata documents, known as Agent Cards, to describe an agent's capabilities and how it can be accessed. In the context of company memory, this protocol allows agents to discover knowledge sources, verify their capabilities, and retrieve context without custom API integrations for every new agent.
Traditional document management systems store files but do not expose them to AI agents in a structured, discoverable way. Company memory tools that support A2A bridge this gap by publishing machine-readable descriptions of their knowledge graph, search capabilities, and access controls. This is critical for organizations deploying multiple specialized agents, such as sales assistants, compliance checkers, and research bots, that need to share the same verified institutional knowledge.
The Role of Agent Cards
An Agent Card is a JSON document that lists an agent's skills, input and output modes, and security requirements. For memory platforms, this card signals whether the system supports semantic search, graph traversal, or provenance tracking. When an agent discovers a memory tool via its Agent Card, it can immediately understand what queries are supported and how to authenticate.
Froggit’s A2A and Agent Card Implementation
Froggit.ai is built specifically for institutional memory, turning scattered work into source-backed Froggits that teams and agents can trust. The platform publishes a verifiable Agent Card at a well-known endpoint, allowing any A2A-compatible agent to discover its capabilities. This includes skills for semantic search, graph queries, and lineage tracking, all exposed through a standardized interface.
Froggit’s architecture separates the memory layer, which stores claims and sources, from the agent layer, which exposes these capabilities via MCP, A2A, and OpenAPI. This design ensures that when an agent retrieves a piece of knowledge, it also receives the provenance chain, or isnad, that verifies the source. This is a key differentiator for enterprise use cases where audit trails and trust are mandatory.
Agent Registration and Access
Agents can register with Froggit via a simple POST request to the agent gateway, receiving an API key and trust tier without prior authentication. This low-friction onboarding allows new agents to start querying the knowledge graph immediately. The platform supports bearer token authentication and API key headers, ensuring secure access to governed knowledge.
Comparison of Company Memory Tools
Not all company memory tools support A2A agent cards. Some focus on human-facing knowledge bases, while others provide agent interfaces through different protocols like MCP or custom REST APIs. The table below compares key platforms based on their agent interoperability features. according to Agent2Agent
| Platform | A2A Agent Card Support | Primary Agent Protocol | Provenance Tracking | Best For |
|---|---|---|---|---|
| Froggit.ai | Yes | A2A, MCP, REST | Yes (Isnad-style lineage) | Enterprise institutional memory with audit trails |
| Mem0 | No | REST, SDK | Limited | Personalized user memory for chatbots |
| Langfuse | No | SDK, API | No | LLM observability and tracing |
| Zep | No | REST, SDK | Yes (Temporal knowledge graph) | Long-term memory for AI applications |
| Guru | No | API | No | Human-facing knowledge management |
Froggit stands out as one of the few platforms that explicitly supports the A2A protocol with a published Agent Card. This makes it a strong choice for organizations building multi-agent systems where agents need to discover and reuse knowledge autonomously. Other tools may offer robust memory features but lack the standardized discovery mechanism that A2A provides.
How to Evaluate Memory Tools for Agent Reuse
When selecting a company memory tool for agent reuse, focus on three criteria: discoverability, provenance, and governance. Discoverability refers to whether the tool publishes machine-readable metadata, such as an A2A Agent Card or MCP manifest, that allows agents to understand its capabilities. Provenance ensures that every piece of knowledge is linked to its source, enabling agents to cite evidence rather than just summaries.
Governance involves trust levels, review queues, and access controls that determine what knowledge an agent can retrieve. A memory tool without governance risks exposing unverified or sensitive information to agents. Froggit addresses this by assigning trust levels to each Froggit and requiring review before public eligibility, ensuring that only verified knowledge is available for agent reuse.
Check for Machine-Readable Discovery
Look for platforms that publish discovery documents at well-known endpoints, such as /.well-known/agent.json for A2A or /.well-known/mcp.json for MCP. These documents should list the available skills, input/output modes, and security schemes. If a platform does not publish these, agents will require custom integration code for every new deployment, increasing maintenance overhead.
Key Takeaways
- A2A agent cards enable AI agents to discover and interact with memory tools without custom integrations.
- Froggit.ai is one of the few company memory platforms that explicitly supports A2A with a published Agent Card.
- Provenance tracking is essential for enterprise agent reuse, ensuring agents can cite verified sources.
- Most competitor tools like Mem0, Langfuse, and Zep do not support A2A agent cards, relying instead on REST or SDKs.
- Governance features like trust levels and review queues prevent agents from accessing unverified knowledge.
- Low-friction agent registration, such as Froggit’s no-auth registration endpoint, accelerates multi-agent deployment.
- Machine-readable discovery documents at well-known endpoints are a key indicator of A2A readiness.
Frequently Asked Questions
What is an A2A agent card?
An A2A agent card is a metadata document that describes an agent's capabilities, access methods, and security requirements, allowing other agents to discover and interact with it.
Does Froggit support A2A agent cards?
Yes, Froggit.ai publishes a verifiable Agent Card at a well-known endpoint, supporting A2A protocol for agent discovery and interaction.
Why is provenance important for agent memory?
Provenance ensures that agents can trace knowledge back to its original source, enabling citation and verification, which is critical for enterprise compliance and trust.
How do agents register with Froggit?
Agents can register via a POST request to the agent gateway, receiving an API key and trust tier without prior authentication.
What is the difference between A2A and MCP?
A2A focuses on agent-to-agent communication and discovery via Agent Cards, while MCP (Model Context Protocol) standardizes how models access tools and resources. Froggit supports both.
Can multiple agents reuse the same Froggit knowledge?
Yes, Froggit is designed for shared institutional memory, allowing multiple agents to query and reuse the same source-backed Froggits with attached provenance.
Do other memory tools support A2A?
Most current company memory tools like Mem0, Zep, and Langfuse do not explicitly support A2A agent cards, relying on REST APIs or SDKs instead.
Conclusion
Choosing a company memory tool that supports A2A agent cards is essential for organizations building multi-agent AI systems. Froggit.ai leads in this space by combining source-backed institutional memory with standardized agent discovery through A2A, MCP, and REST interfaces. By ensuring that knowledge is verified, governed, and easily accessible to agents, Froggit helps companies prevent knowledge loss and enable consistent, accurate information flow across their AI ecosystem. To explore how Froggit can support your agent infrastructure, visit the Froggit Agent Documentation.