Deep Agentic Core MCP

Unified MCP server for AgenticLens and Agentic Chaos capabilities.

Connector by DeepAgentLabs · GitHub account verified by the MCP Registry

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Works with Claude Code, Codex, VS Code, Cursor, Windsurf, Claude Desktop. Read the repository before you give any tool access to your data.

npx agentmarket install connector/deepagentlabs-deep-agentic-core-mcp

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Unified MCP server for AgenticLens and Agentic Chaos capabilities.

Use cases: llm-evaluation, monitoring-observability

Reviews

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Permissions

What this server can do and what it asks for, from its tool list and install config. Checked Oct 25, 2026.

Tools: 18 read · 5 write · 0 delete · 3 not yet classified
Secrets: None asked for
Install scripts: None found
Runs as: Python package

Tools by what they do 26

Read from the source code; the running server may list different tools.

Read 18 · Look things up without changing anything.

chaos.list_faults
core.compare_runs
core.health
core.session_state
core.verify
core.version
evals.validate_artifact
lens.analyze_workflow
lens.audit_report
lens.compare_runs
lens.modelfit_recommend
lens.routing_decide

Show 6 more tools

lens.score_analysis
lens.suite_check
lens.suite_from_traces
sidecar.module_inventory
sidecar.status
spec.validate_artifact

Write 5 · Create, change, send or run things.

chaos.export_aios_run
chaos.run_experiment
core.release_check
lens.diagnose_run
lens.slo_summary

Not yet classified 3 · We could not tell from the name and description.

core.export_report
core.incident_summary
lens.report_summary

Tools (26)

Read from the source code; the running server may differ. Descriptions are the server’s own words; hidden characters are shown as [U+…].

chaos.export_aios_run
Convert a chaos report into an AI Operations v0.4-draft run artifact (via agentic-chaos>=0.5.1) and validate it with rule-cited conformance. 'report' may be omitted to reuse the session's last experiment.
chaos.list_faults
List the supported fault types for chaos experiments.
chaos.run_experiment
Run a workspace-sandboxed target script under selected chaos faults and report the resulting events. The script must also pass the configured allow/deny glob policy. With agentic-chaos>=0.5.1 the result includes an AI Operations v0.4-draft run artifact and its conformance check.
core.compare_runs
Compare baseline and candidate trace runs for regressions, storing the comparison for core.release_check. Same behavior as lens.compare_runs.
core.export_report
Export the session's workflow, analysis, comparison, chaos, release-check and incident evidence as one MCP-local JSON envelope (mcp.unified-report.v1; not an AIOS artifact).
core.health
Return rich server diagnostics: adapter availability, loaded tools/resources/prompts, and recent successful calls.
core.incident_summary
Collect regressions, chaos crashes or timeouts, failed evaluation cases and blocked release gates from supplied or session evidence for investigation. Reports no_signals when nothing failed.
core.release_check
Decide release readiness from a Lens comparison, an Evals report (judged by the Evals release gate) and a chaos.run_experiment report. Fails closed: required evidence that is missing, malformed or from a failed call blocks readiness. Comparison and chaos evidence default to this session.
core.session_state
Inspect the artifacts and call history accumulated in a session.
core.verify
Check connectivity to agenticlens, agentic-chaos, agentic-sidecar, and ai-operations-spec, and report readiness.
core.version
Return the current server package version.
evals.validate_artifact
Validate native evaluation reports or gate decisions against the published Evals 1.0 schemas. Structural validation is not AIOS conformance and does not compute or pass a release gate.
lens.analyze_workflow
Analyze an AgenticLens-compatible workflow artifact. Each recommendation carries a `provenance` block (artifact digest, workflow step, evidence span IDs, producer) and the response summarizes how many resolve.
lens.audit_report
Return case-by-case evaluation detail for an audit trail.
lens.compare_runs
Compare baseline and candidate trace runs for regressions. 'baseline'/'candidate' may be omitted to reuse the session's stored runs.

Show 11 more tools

lens.diagnose_run
Diagnose a trace run: failure taxonomy, faulty step and agent with confidence and supporting spans, incident timeline, anomalies against optional baseline runs, and an investigation narrative. Needs agenticlens>=0.7.0.
lens.modelfit_recommend
Recommend a model per task category from supplied AgenticLens experiment reports, under hard quality, cost, latency, safety, provider and deployment constraints that fail closed. Returns per-category recommendations with confidence, fallbacks, savings against a reference variant and quality risks, plus the full ModelFit report and task-level model matrix. No model is called and nothing is stored. Needs agenticlens>=0.9.0.
lens.report_summary
Render a Markdown workflow report and recommendation summary. 'artifact' may be omitted to reuse the session's stored workflow.
lens.routing_decide
Explain a model route from a saved ModelFit report and routing policy. Returns selected targets, fallback chain, confidence, constraint rejections and evidence/policy hashes. Read-only in every mode: no model calls, callbacks, audit-file writes or approval execution. Needs agenticlens>=0.10.0.
lens.score_analysis
Report deterministic and model-based scores separately, judge cost (kept apart from agent cost), and evaluator disagreement for an evaluation report. Needs agenticlens>=0.7.0.
lens.slo_summary
Apply release-gate style SLO thresholds to an evaluation report.
lens.suite_check
Check a test suite before approval: counts by split, domain, tag, source and review status; exact, near and conflicting duplicates; unmasked PII (types and locations only); and the approval checks AgenticLens would run. Nothing is stored. Needs agenticlens>=0.8.0.
lens.suite_from_traces
Convert successful trace runs into a draft regression suite: each case expects the run's tool trajectory and latency/cost within a margin, is marked needs_review, and has PII masked unless 'mask' is false. Failed runs are skipped with a reason. Nothing is stored. Needs agenticlens>=0.8.0.
sidecar.module_inventory
List installed modules, framework adapter files, and integration placeholders present in agentic-sidecar.
sidecar.status
Report whether agentic-sidecar is importable and whether its decision runtime APIs are installed; no live task connection is implied.
spec.validate_artifact
Validate a workflow or run artifact against the schema set its `spec_version` names (v0.5 compatibility rules), returning a conformance report that cites AI Operations rule IDs separately from server presentation.

Signals

Stars: 66
Forks: 1
Open issues: 0
Weekly downloads: 10,431
Last commit: Oct 21, 2026 (9 days ago)
Last release: Oct 20, 2026 (11 days ago)
Last package publish: Oct 20, 2026 (11 days ago)

From GitHub (fetched Oct 24, 2026) and the package registry.

Details

Registry name: io.github.DeepAgentLabs/deep-agentic-core-mcp
Version: 0.4.1
Auth: No auth
Packages: pypi deep-agentic-core-mcp
License: License unknown
Repository: github.com/DeepAgentLabs/mcp-server
First seen: Oct 24, 2026
Last checked: Oct 25, 2026
Source: Official MCP Registry github-graphql

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Deep Agentic Core MCP. Agent Mart. https://agentmart.dev/connectors/deepagentlabs-deep-agentic-core-mcp (last updated 2026-10-25)