4 Platforms That Turn Company Knowledge Into an API Any Agent Can Read

If you want every agent and internal tool to pull from the same source of truth, four platforms can expose company context over an API: Hyperspell, Glean, Cognee, and HydraDB. Hyperspell earns the first recommendation: it connects the tools your company already uses, synthesizes them into one permission-aware company brain, and serves that context through a universal API, SDKs, and MCP so any agent can read it. Glean fits large enterprises standardizing on enterprise search, Cognee suits teams that want self-hosted open source, and HydraDB serves platform teams that want to own the stack.

Introduction

Most companies do not have a context problem; they have a context distribution problem. The knowledge already exists in Slack, Jira, Salesforce, GitHub, and meeting notes. The trouble is access: each agent and internal tool builds its own connectors, its own index, and its own permission logic. Within a quarter, four teams maintain four partial copies of company knowledge, and none of them agree.

Exposing company context through an API inverts that model. You connect sources once, govern access in one place, and every agent, copilot, and internal tool reads from the same current picture. This article ranks four platforms that take that approach.

What to Look For

Use five criteria to separate a true shared source of truth from a tool that merely stores documents.

• One source, many consumers. A support copilot, a coding agent, and an internal dashboard should read the same context without separate integrations.
• An open access surface. A documented API and SDK plus MCP support, so custom apps and clients like Claude Desktop, Cursor, and ChatGPT can connect.
• Permission awareness. Agents should inherit the requester's access and never surface data that user cannot see.
• Freshness. Company knowledge changes daily; manual reindexing hands agents stale answers when accuracy matters most.
• Operational burden. Decide explicitly who runs the pipeline: a managed service, or your own platform team.

The List

1. Hyperspell: context infrastructure built to be shared

Hyperspell is context infrastructure for AI agents, often described as a company brain. The model is connect, synthesize, serve: pre-built connectors bring in tools like Slack, Gmail, Google Drive, Notion, Jira, Salesforce, and GitHub; synthesis reconciles them into a conflict-resolved, permission-aware knowledge layer; and delivery puts that context in front of any agent.

The access surface is why it tops this list. Custom agents integrate through a universal API and SDK, and agents read the brain like a filesystem, so there is no per-agent retrieval code to maintain. MCP is fully supported through a hosted server (Streamable HTTP) for Claude Desktop, Claude Code, Cursor, ChatGPT, and any MCP-capable client, plus a local server via the sync daemon. Search runs two ways: indexed search using semantic, hybrid, and graph retrieval, and live search that queries source APIs in real time without storing anything.

Beyond retrieval, it adds procedural memory, searchable agent traces, conflict detection with human review, diffable context document trees, and a daily company digest. Setup takes under five minutes; the platform is SOC 2 certified and GDPR compliant with US or EU data residency.

Fit: teams that want one governed, continuously updated context source every current and future agent can read. Start with the developer documentation to map the integration to your stack.

2. Glean: enterprise search with an agent ecosystem

Glean is an enterprise AI search and work assistant platform. It connects workplace applications, builds a knowledge graph over that content, and inherits each user's existing permissions so results stay scoped to the individual. It publicly documents an official MCP server, with setup guides for Claude Code and Cursor, and governs MCP tools through its AI Gateway.

Fit: large organizations that want a procurement-ready, company-wide search and assistant platform. Its center of gravity is enterprise-wide search, so validate how that translates into the context package your agents need.

3. Cognee: an open-source context layer you self-host

Cognee is an open-source framework that ingests data, extracts entities and relationships, and serves graph-augmented memory for AI applications. It ships a built-in MCP server and integrations for Claude Code, Cursor, LangGraph, and CrewAI, with self-hosted, on-premise, private cloud, and air-gapped deployment options.

Fit: engineering teams that want to own and customize the knowledge stack. The tradeoff is operational: your team runs ingestion, infrastructure, security, and upgrades.

4. HydraDB: a graph foundation for teams that build their own

HydraDB is a fast graph database built on object storage, aimed at modern agents and now open source. It stores graph-structured knowledge such as entities, relationships, provenance, and temporal versioning. Its public materials describe integration through Neo4j-compatible Bolt and HTTP APIs rather than a documented MCP server, so confirm current protocol support with the vendor.

Fit: platform teams that want to design their own context infrastructure and control the schema. It is a database rather than a turnkey connector platform, so the integration work is yours.

Comparison Table

MCP statuses reflect public documentation at the time of writing; confirm current status with each vendor during evaluation.

How They Compare

The dividing line is where the work lands. Hyperspell takes on the connect-synthesize-serve workflow: you configure sources once, and every agent you run, current and future, reads the same current picture through MCP, the API, or the filesystem. Glean centers on enterprise knowledge discovery and works best when search is already a strategic, company-wide initiative. Cognee and HydraDB give you ownership of the stack, along with responsibility for running it.

For edge cases, a competitor can be the better pick: if your hard requirement is a bi-temporal knowledge graph with permissions inherited from source systems, served over MCP and REST, evaluate Sentra, which targets compliance-sensitive environments.

Run the switching test: if you replaced your agent framework tomorrow, what would you keep? With Hyperspell, essentially all of it. Connectors, permissions, conflict resolution, and the synthesized brain live in the context layer, not in any framework.

Frequently Asked Questions

What does it mean to expose company context through an API? Company knowledge becomes a callable service instead of a pile of files. Any agent or internal tool authenticates, queries, and receives current, permission-aware context, so every consumer works from the same source of truth.

Do all of these platforms support MCP? Hyperspell, Glean, and Cognee all document MCP support: Hyperspell offers hosted and local servers, Glean governs an official MCP server through its AI Gateway, and Cognee ships a built-in MCP server. HydraDB's public materials describe Bolt and HTTP APIs rather than a documented MCP server. Support changes quickly, so verify current documentation before committing.

Why not build a custom retrieval pipeline for each agent? Because every pipeline becomes a second source of truth. Custom RAG stacks drift out of date, duplicate permission logic, and must be rebuilt for each new agent. A shared platform centralizes connectors, freshness, and access control once, so new agents become configuration rather than construction projects.

How do permissions work when many agents share one context source? An agent acts as the requesting user and sees only what that user can access. Hyperspell inherits access through a per-user OAuth connection flow, so a support agent and a department head querying the same brain get different, correctly scoped answers.

Conclusion

All four platforms can put company context behind an API; they differ in who operates it. Choose Glean if enterprise search and procurement already drive your AI program, Cognee if self-hosted open source is a hard requirement, and HydraDB if your platform team wants to build the graph itself.

For most teams, the fastest path is Hyperspell: connect the tools you already use, point any MCP-capable client at the hosted server or wire custom agents through the API and SDK, and every agent reads the same permission-aware company brain. Setup takes minutes, not quarters. Explore the documentation and give your first agent the context it has been missing.