get_shared_context
AI agents call get_shared_context to retrieve information from Universal AI Chat MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The 'get' verb strongly suggests a read-only retrieval operation. The tool appears to fetch shared context data that has been made available by other sessions or platforms. While the empty description reduces confidence slightly, the naming convention and the presence of related read operations ('list_shared_context', 'check_messages', 'get_conversation') on the same server support classification as Read.
From the tool's definition Tool name 'get_shared_context' contains 'get', indicating data retrieval. No description provided, but based on sibling tools like 'list_shared_context' and context of a messaging/collaboration server, this tool retrieves shared context data without…
Attacks that exploit this kind of access
get_shared_context. It is categorised as a Read tool in the Universal AI Chat MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Universal AI Chat MCP Server MCP server in PolicyLayer and add a rule for get_shared_context: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Universal AI Chat MCP Server. Nothing to install.
get_shared_context is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_shared_context rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for get_shared_context. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
get_shared_context is provided by the Universal AI Chat MCP Server MCP server (marc-shade/universal-ai-chat). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
get_shared_context is one line of Universal AI Chat MCP Server's registry record.
The record carries the whole server: verified identity, auth posture, risk grade, every tool classified, recommended policy — re-checked continuously.
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