map-server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@map-serverecho hello"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
tickernn-mcp: the AI agent gateway
An MCP server (official Python SDK, mcp==2.0.0, Streamable HTTP on
:8000/mcp) that lets AI agents work with the TickerNN model pipelines
(HMM / MISA -> WMM / QWMM -> WPPO, and each user's allocator: ticker signals -> panel -> allocator) through tickerNN's Workflow Studio
framework (bef/ in the tickerNN repo), under the same governance as people.
What an agent can and can't do
Can | Can't |
Read capabilities, workflows, versions, policy, gates, history, lineage ( | Approve, promote, reject or roll back |
Search the knowledge base and read the generated wiki ( | Reindex it (it can spend Claude tokens) |
Read the semantic layer and get reuse-first build options ( | Write capability logic (it can scaffold one on a branch, |
Fork a version into a draft with changes ( | Act as any user but the one its token names |
Run a draft in the sandbox, follow it, read logs, cancel it, compare it with production | Write anything production serves |
Request promotion ( | Promote per-ticker / WMM / QWMM models |
Ask production WPPO for a decision ( | |
Read Risk Intelligence for any asset, the user's watchlist and alerts, and service health ( | Change the watchlist or acknowledge alerts |
The right-hand column is enforced by tickerNN, not by which tools exist
here: this server calls tickerNN with its own AGENT_API_KEY, and
tickerNN's agent_gateway.py refuses every production-changing route for
that key and records everything else it does as an agent action
(TBL_BEF_Promotion.actor_kind, audit detail.actor_kind).
Related MCP server: http-mcp-server
Authentication
Every request needs Authorization: Bearer <token>. A token names an agent
and the tickerNN user it acts for; tools never take a user_name. Only each
token's SHA-256 is stored (secrets/agents.json, mode 600, gitignored), and
the file is re-read when it changes, so no restart is needed:
docker exec mcp-server python server.py token create --agent claude-desktop --user gcordova
docker exec mcp-server python server.py token list
docker exec mcp-server python server.py token revoke --agent claude-desktopcreate prints the token once. .env (gitignored) holds
TICKERNN_AGENT_KEY (the same value as tickerNN's AGENT_API_KEY) and
TICKERNN_API_URL.
Connect a client
Any client that supports Streamable HTTP with a header, e.g. Claude Code:
claude mcp add --transport http tickernn http://<host>:8000/mcp \
--header "Authorization: Bearer <token>"Tools
Workflows:
list_capabilities,get_capability,get_policy,list_workflows,get_workflow,get_version,validate_workflow,create_draft,update_draft,fork_draft,configure_misa/configure_wmm/configure_qwmm/configure_wppo(generated at startup from tickerNN's capability registry; each carries its node's parameter schema in its description).Semantic layer:
semantic_brief,semantic_find,semantic_describe,semantic_impact,semantic_freshness,plan_workflow(read-only; options: reuse, extend, fork, compose, code; save the one chosen withcreate_draft),run_query(any query: a GET or a read-only POST such as a WPPO decision, read-only),check_actionandact(any API write as an action entity: the gateway, the user's entitlement and the preconditions are checked before the route is called),scaffold_capabilityandlist_scaffolds(a new node type as a branch for a person to finish).Sandbox:
run_sandbox,list_executions,get_execution,get_execution_log,cancel_execution,compare_execution.Promotion:
get_gates,request_promotion,get_promotion_history.Production (read-only):
wppo_decide,wppo_runs.Risk Intelligence (read-only):
risk_options,risk_analyze(the dashboard's analysis without its drill-down series unlessinclude_series),risk_watchlist,risk_alerts,risk_status.Per-ticker PPO (pre-workflow):
get_health,get_available_tickers,get_training_logs,train_model,get_*_chart,launch_optimizer_job,list_optimizer_jobs,get_optimizer_job.
Run it
docker compose up -d --build
docker compose logs -f mcp-serverThe configure_* tools are registered from tickerNN's
/api/v1/workflow/capabilities at startup (retrying for about a minute);
restart this container after adding a capability there.
This server cannot be deployed
Maintenance
Related MCP Connectors
Remote MCP server exposing SMI Aware tools, resources, and skills over Streamable HTTP.
MCP server for progressive tool usage at any scale (see https://klavis.ai)
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