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You can share skill content and manage one canonical list of MCP servers across Claude Code, Codex, Cursor, and Hermes Agent—but the available documentation does not show a single MCP configuration file that all four read unchanged with zero setup. A workable approach is to keep shared skills and server intent in one place, then use the file format and locations each agent expects.
What can actually be shared?
MCP is the connection layer that lets an agent use external tools. The server configuration is client-specific: Cursor documents JSON files, Hermes documents YAML, and OpenAI publishes separate Codex guidance. Skill content is more portable, but each client still determines which directories it discovers.
That distinction matters: one shared source of truth is a practical team design, not a documented guarantee that the four agents automatically synchronize. Keep the desired servers and reusable skill instructions together, then adapt or generate each client’s configuration as needed.
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How the four agents handle configuration
| Agent | Documented sharing or configuration detail | Practical limit |
|---|---|---|
| Claude Code | Hermes documents importing a Claude Code mcpServers block, along with associated skills and instructions. |
The documented import is into Hermes; it does not establish universal or two-way synchronization. |
| Codex | OpenAI provides separate documentation for Codex MCP configuration and building Codex skills. | These sources do not establish that Codex reads the settings files of the other agents. |
| Cursor | Cursor documents project-level .cursor/mcp.json and user-level ~/.cursor/mcp.json. Its skills documentation covers .agents/skills/ and discovery of compatible Claude and Codex skill directories. |
MCP configuration remains in Cursor’s documented locations. Personal skill locations and Cloud Agent syncing are separate concerns. |
| Hermes Agent | Hermes reads MCP configuration under mcp_servers in ~/.hermes/config.yaml, supports stdio and HTTP servers, and documents importing from Claude Code. |
Its YAML structure differs from Cursor’s JSON and Claude Code’s mcpServers shape. |
Sources: Hermes MCP documentation, Cursor Skills, Cursor MCP, and OpenAI Codex MCP.
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Build a shared setup without assuming zero config
A practical team arrangement is a version-controlled collection of portable Markdown skills plus a canonical inventory of intended MCP servers. Keep each agent’s required settings file alongside it, or generate those files from the inventory. This is a recommendation based on the documented format differences, not a vendor-provided universal generator.
- Put reusable instructions in Markdown skills. Use a shared project location where the clients you use can discover it. Cursor documents
.agents/skills/and compatible Claude and Codex skill directories; check each target client’s current discovery rules rather than assuming identical behavior. - Record server intent once. For each MCP server, track its name, transport, endpoint or command, and authentication requirements. Treat this as the team’s canonical inventory, not as a configuration file that every agent can necessarily load.
- Provide the client-specific configuration. Maintain or generate the JSON, YAML, or other settings each agent expects. Review the resulting files for correct paths, transport details, and authentication handling before relying on them.
- Check where the configuration applies. A project file can travel with a repository, while a user-level file applies to an individual’s environment. Cursor’s documentation distinguishes project and user MCP locations; it also notes that personal skills need syncing for Cloud Agents.
- Validate discovery and access. Confirm that each agent sees the intended skills and can connect to each server in the environment where it will run, including remote or cloud sessions if applicable.
Use Hermes’ Claude Code import when it fits
Hermes documents hermes import-agent claude-code as a migration route for Claude Code MCP settings, skills, and instructions. It is a concrete shortcut if the source is Claude Code and the destination is Hermes. It should not be treated as a universal importer for Codex or Cursor.
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See the Hermes MCP documentation for the import and supported MCP setup details.
Choose a sharing approach
| Approach | What it means | Trade-off |
|---|---|---|
| Duplicate settings manually | Configure each agent separately, while keeping skill files shared where supported. | Simple to start, but changes to server settings must be repeated and kept consistent. |
| Canonical inventory with per-agent files | Maintain one list of intended servers and separate configuration files in each agent’s expected format. | Balances central oversight with client-specific configuration, but requires maintaining the mappings. |
| Generate per-agent files | Use a team-built process to produce client-specific settings from the canonical inventory. | Can reduce repetitive edits, but the reviewed documentation does not establish an off-the-shelf generator that supports all four agents. |
Choose based on shared skill discovery, MCP formats, project versus user scope, cloud or remote synchronization, migration or generation support, and each server’s transport and authentication requirements. The sources describe client-specific capabilities; they do not establish that any approach works without setup across every version and environment.
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Check before relying on a shared setup
- Verify the MCP configuration path and format for each agent and version you deploy.
- Confirm the server’s transport and authentication method are supported in the target environment.
- Check which skill directories the client discovers, including whether a skill is project-level or personal.
- For cloud or remote agents, verify that both the required skills and server access are available there; local files alone may not provide them.
- Test the exact setup your team will use before describing it as zero-config.
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