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Create, sign, and enforce binding agent agreements with deadlines and penalties.
This MCP tool does not declare any required secrets or remote endpoints, and it is open source under MIT with no obvious high-risk red flags. However, the documentation is minimal, the README is absent, and it has local code-execution capability, so it should be integrated with caution.
The material explicitly states that no keys or environment variables are required, and there is no indication that users must provide API keys, access tokens, or account credentials. Based on the available information, credential exposure or abuse risk appears low.
The material explicitly lists no remote host endpoints, and the description does not indicate that contract content or user data is sent to external services. Based on the provided information, there is no clear data egress path.
The system checks mark this tool as executes-code, indicating that the MCP server has the standard ability to execute code or run processes locally. This is an inherent MCP risk surface and warrants a least-privilege runtime, but the material does not show requests for system privileges beyond its stated purpose.
The description suggests it handles business data such as agreements, signing, and lifecycle state, which implies access to user-provided contract text and related metadata. However, the missing README leaves local file, directory, or resource access boundaries undocumented, so this area warrants caution.
On the positive side, it is open source under the MIT license, so the code is in principle auditable, which materially lowers supply-chain risk. However, it comes from a third-party registry, has 0 stars, unknown maintenance status, and no README, indicating weak maturity and maintenance signals; a basic code and dependency review is advisable before adoption.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "AgentContract MCP Server" yet — see the docs or source repo.
Create a collaboration contract for two AI agents: a research agent must deliver a competitor analysis report within 48 hours, and a writing agent must produce a product announcement draft within 24 hours after research is complete; record breaches for delays, and include lifecycle states and acceptance criteria.
A structured agent contract with roles, deliverables, deadlines, penalty rules, acceptance criteria, and lifecycle states.
Submit an existing agent contract for signing by the participating AI agents, then update its status to active and return each signer, signing time, and the current contract state.
A signing result and state update record confirming the contract is active and ready for execution.
Check an active agent contract: if the research agent misses the deadline without delivering, mark a breach, enforce the predefined penalty, and output the full event log and current contract state.
A breach determination, penalty execution result, event log, and the updated contract lifecycle state.
Create, manage, and compose AI agents for MCP-compatible clients and tools.
Orchestrate multiple AI agents in real time and monitor tasks and artifacts.
Protect AI agent payments with escrow, risk scoring, and dispute resolution.
Coordinate multiple AI agents on software projects with shared tasks and context.
Run deterministic agent orchestration with task decomposition, subagents, and review feedback.
Coordinate AI agents through negotiation for more efficient automated workflows.