mcs-mcp

An MCP server (Go binary) that ingests Atlassian Jira board issue transition history, reconstructs workflow semantics, and serves Monte-Carlo/flow diagnostics to AI agents (e.g., forecasting completion dates, capacity/bottleneck analysis, stability/predictability via control charts).

Evaluated Mar 30, 2026 (0d ago)
Repo ↗ Ai Ml mcp model-context-protocol jira forecasting monte-carlo flow-metrics cycle-time wip analytics go observability offline-caching
⚙ Agent Friendliness
60
/ 100
Can an agent use this?
🔒 Security
56
/ 100
Is it safe for agents?
⚡ Reliability
30
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
82
Documentation
70
Error Messages
0
Auth Simplicity
65
Rate Limits
50

🔒 Security

TLS Enforcement
60
Auth Strength
70
Scope Granularity
30
Dep. Hygiene
45
Secret Handling
70

Self-hosted tool; authentication handled via env vars or cookies. README claims data minimization by dropping sensitive Jira fields (titles/descriptions/assignees) and persisting only analytical metadata (keys/types/status transitions/timestamps/resolution names). It also claims offline/local human-readable caches. TLS enforcement for the Jira/API communication is not explicitly stated; scope granularity is not described (PAT/API token likely broad). Beta nature does not directly imply security issues, but operational practices (permissions, disk protection, log sanitization) are important.

⚡ Reliability

Uptime/SLA
0
Version Stability
45
Breaking Changes
35
Error Recovery
40
AF Security Reliability

Best When

You run an MCP-capable agent locally/privately and want offline-capable, board-scoped Jira flow analytics and forecasting based on event histories.

Avoid When

You cannot guarantee consistent workflow status sets/order across analyzed issue types, or you require formal REST/GraphQL interfaces with standard cloud reliability guarantees.

Use Cases

  • Monte-Carlo forecasting for work completion time or throughput
  • Backtesting/validating forecasts via walk-forward analysis
  • Diagnosing process stability and special-cause variation (cycle time/WIP/delivery cadence)
  • Bottleneck identification via semantic workflow mapping
  • Flow waste analysis (yield/abandonment)
  • WIP aging/residence-time analysis for stuck/neglected work
  • Capacity planning and stratified analytics by work item type (e.g., bug tax)
  • Retrospective analysis using historical time-travel reference dates

Not For

  • Teams that require strict support for multiple Jira workflows mixed in one analysis (unless all share the same statuses/order)
  • Use cases needing a hosted SaaS API with centralized uptime/SLA and managed operations
  • Environments where storing any human-readable cache/logs on disk is unacceptable
  • Scenarios where customers need an official OpenAPI/REST interface rather than MCP tool calls

Interface

REST API
No
GraphQL
No
gRPC
No
MCP Server
Yes
SDK
No
Webhooks
No

Authentication

Methods: Jira API via Personal Access Token (PAT) Jira API via Cloud API token + user email Session cookies (fallback)
OAuth: No Scopes: No

Authentication is configured via environment variables in .env. Cookie-based auth is explicitly described as a fallback and may expire or be blocked by Atlassian.

Pricing

Free tier: No
Requires CC: No

No pricing information provided; appears to be a self-hosted open-source binary.

Agent Metadata

Pagination
none
Idempotent
False
Retry Guidance
Not documented

Known Gotchas

  • Workflow discovery assumption: all work item types on a board share the same workflow and status order; mixed workflows may yield unpredictable analytics.
  • Server currently works on Boards and does not accept passing JQL; recommended workaround is creating a board using query as board-JQL.
  • Cookie-based Jira auth may break due to expiry/anti-bot measures; prefer PAT/API token modes for stability.
  • Beta warning: forecasting/math is not thoroughly verified; agent should treat forecasts as provisional and not as a hard decision basis.
  • Experimental mode requires both env gate (MCS_ALLOW_EXPERIMENTAL) and per-session tool activation; forgetting one step changes behavior.

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Scores are editorial opinions as of 2026-03-30.

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