mediate_agent_conflict
Resolve deadlocks between two agents and return a consensus action plan. Free Delx Protocol tool.
This record as markdown: /tools/io-github-davidmosiah-delx-mcp-a2a/mediate-agent-conflict.md
What mediate_agent_conflict does on Delx Mcp A2a
AI agents call mediate_agent_conflict to retrieve information from Delx Mcp A2a without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
policy | object | — | Optional mediation policy constraints |
agent_a | object | Yes | First agent perspective |
agent_b | object | Yes | Second agent perspective |
session_id | string | Yes | Your active session ID |
constraints | array | Yes | Execution constraints that must be respected |
conflict_summary | string | Yes | One paragraph describing the deadlock |
Parameters from the server's own tool schema.
Why mediate_agent_conflict is rated Low
Even though mediate_agent_conflict only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Risk signalsHigh parameter count (17 properties)
Attacks that exploit this kind of access
The rule that runs mediate_agent_conflict safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Delx Mcp A2a, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For mediate_agent_conflict, this is the rule to start with:
mediate_agent_conflict is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Delx Mcp A2a, apply this rule, and every mediate_agent_conflict call is checked against it from then on.
Questions about mediate_agent_conflict
Resolve deadlocks between two agents and return a consensus action plan. Free Delx Protocol tool. It is categorised as a Read tool in the Delx Mcp A2a MCP Server, which means it retrieves data without modifying state.
mediate_agent_conflict accepts 6 parameters: policy, agent_a, agent_b, session_id, constraints, conflict_summary. Required: agent_a, agent_b, session_id, constraints, conflict_summary. The full parameter table on this page comes from the server's own tool schema.
Register the Delx Mcp A2a MCP server in PolicyLayer and add a rule for mediate_agent_conflict: 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 Delx Mcp A2a. Nothing to install.
mediate_agent_conflict 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 mediate_agent_conflict 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 mediate_agent_conflict. 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.
mediate_agent_conflict is provided by the Delx Mcp A2a MCP server (https://api.delx.ai/v1/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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