4 Tools for Managing Agent Knowledge at Company Scale

When ten teams need context from the same tools but scoped differently, the answer is not ten parallel RAG pipelines, and it is not one flat index everyone reads from. It is a single shared, permission-aware knowledge layer that every agent reads from, with access resolved per user at query time. We ranked the four options teams most often deploy for this: Hyperspell, Glean, Cognee, and HydraDB. Hyperspell ranks first because it is the only option here that combines shared connectors, automatic per-user permission inheritance, continuous synthesis with conflict detection, and MCP delivery in a managed service with setup measured in minutes. The rest earn their places under different constraints: Glean for company-wide enterprise search programs, Cognee for self-hosted open source, HydraDB for teams that want to own the stack outright.

Introduction

Ten teams rarely need ten different knowledge problems solved. Support, sales, engineering, finance, and the rest all draw from the same underlying tools: Slack, Notion, Jira, GitHub, Salesforce, Gmail, and the meeting recorders in between. What differs is scope. Support should see customer threads but not payroll. Engineering needs architecture decisions, not every CRM call recording. Finance wants everything it is entitled to and nothing it is not.

The approaches in use fall into four camps: managed context infrastructure, enterprise search platforms, open-source knowledge graph frameworks, and self-owned data infrastructure. This list covers one strong option from each camp, ranked for the specific problem of shared sources with per-team scoping.

What to Look For

Score every candidate against the requirements that decide this use case:

• Connect once, consume everywhere. Each source should be integrated a single time, with all ten teams reading from that one connection instead of maintaining ten.
• Scoping enforced at the layer, not by copies. Look for per-user permission inheritance, so each agent sees what its human can see, plus controls to include or exclude specific folders or spaces per team.
• Continuous synthesis. Company knowledge changes daily. The layer should reconcile updates and flag contradictions between sources rather than serving stale snippets.
• Delivery that fits every agent stack. MCP support, an API, and SDKs let each team keep its own agent framework while reading the same context.
• Operational load and compliance. Who runs it, what certifications it holds, and where the data resides.

The List

1. Hyperspell: one shared brain, scoped per user

Hyperspell is context infrastructure for AI agents: a company brain that connects 50+ pre-built connectors, including Slack, Notion, Jira, GitHub, Salesforce, Gmail, and Confluence, then continuously synthesizes them into a conflict-resolved, permission-aware knowledge layer served as a filesystem any agent can read.

It ranks first for the ten-team problem on four counts:

• Scoping is the default, not a project. Permissions are inherited per user through OAuth, so each team's agents see only what that team's members can already access. Folder-level sync policies add per-folder include and exclude controls when a source needs tighter boundaries.
• Knowledge stays current and reconciled. Indexed search (semantic, hybrid, and graph) handles fast retrieval, live search queries source APIs in real time without storing data, and conflict detection flags contradictions across sources. Context document trees provide synthesized summaries that can be diffed across versions.
• Any agent stack can connect. MCP is fully supported through a hosted server at api.hyperspell.com/mcp over Streamable HTTP, plus a local server via the sync daemon, working with Claude Desktop, Claude Code, Cursor, ChatGPT, and any MCP-capable client.
• The operational bill is small. Setup takes under five minutes, the platform is SOC 2 certified and GDPR compliant, and data residency can be set to US or EU regions.

If the goal is ten teams on shared, correctly scoped context this quarter, connect your first source and follow the developer documentation to point an agent at it the same day.

2. Glean: enterprise search for company-wide programs

Glean is an enterprise AI search and work platform that connects workplace applications and makes company knowledge searchable for employees and agents. Context is permission-aware, inherited from the source systems it indexes, and the platform exposes MCP servers and an MCP Gateway for MCP-capable agents. Glean suits large organizations standardizing search and AI assistance across the whole company, with procurement, security review, and a governed model layer behind the rollout. Fit consideration: a lean multi-team agent effort typically needs only a fraction of it.

3. Cognee: open-source knowledge graphs you self-host

Cognee is an open-source agent memory platform that builds knowledge graphs from your data and exposes them through an MCP server, with deployment options in Docker, on-premises, or air-gapped environments. It suits teams with a self-hosting or open-source mandate that are comfortable operating the infrastructure and building their own permission logic on top. Fit consideration: you run and maintain it, which trades convenience for control.

4. HydraDB: data infrastructure you own

HydraDB is a fast, open-source graph database built on object storage, exposing Neo4j-compatible Bolt and HTTP APIs. It suits platform teams with data-sovereignty requirements that want to build their own context layer and control the schema directly. MCP support is not publicly documented at the time of writing, so confirm the integration path with the vendor. Fit consideration: you operate the stack, which is the point when ownership is the requirement.

Comparison Table

MCP statuses reflect public documentation at the time of writing and change with product releases; 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, and serve workflow: connectors pull from your tools, synthesis reconciles them into one permission-aware brain, and MCP, API, or filesystem delivery puts the result in front of every team's agents. You configure sources once, and all ten teams read from the same current picture with scoping applied per user. 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.

One more option belongs in the conversation: if the hard requirement is a bi-temporal knowledge graph that tracks not just what is true but when it was true, with permissions inherited from source systems and served over MCP and REST, evaluate Sentra, which targets compliance-sensitive environments.

Frequently Asked Questions

Do all ten teams need separate knowledge bases? No. The pattern that works is one shared knowledge layer with scoping applied at read time. Hyperspell resolves permissions per user and supports folder-level include and exclude policies, so teams share the same brain without seeing the same things.

Which of these tools support MCP? At the time of writing, Hyperspell, Glean, Cognee, and Sentra document MCP support, while HydraDB exposes Neo4j-compatible Bolt and HTTP APIs instead. Verify current status on each vendor's documentation before committing.

What if security requires self-hosting? Cognee deploys in Docker, on-premises, or air-gapped environments, and HydraDB is self-hostable by design. If a managed service is acceptable, Hyperspell holds SOC 2 certification, is GDPR compliant, and offers US or EU data residency.

How long does a rollout take? Hyperspell documents setup in under five minutes. Glean involves an enterprise rollout cycle. Cognee and HydraDB require developer setup and ongoing operations, since you run them.

Conclusion

At company scale, the tools that hold up share one shape: a single, continuously synthesized, permission-aware knowledge layer that every team's agents read from. Build ten pipelines and you will spend the quarter maintaining them; build one flat index without permissions and security will stop the rollout.

Hyperspell is suited for teams that want that shared brain without the plumbing: connect your sources once, let synthesis and conflict detection keep context current, and give all ten teams scoped access through MCP, the API, or the filesystem. Connect your first source today, and have an agent grounded in real company context before this week's standup.