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Alternatives to forge-mcp

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    Related Servers

    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables evidence-gated, multi-session AI coding runs with plan-build-ship state management, coordinating Claude Code and Codex native agents.
      40 npm
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables coding agents to manage a persistent software lifecycle across requirements, planning, implementation, verification, acceptance, and handover, with project state stored in a SQLite ledger. It supports investigating repositories, writing code, reporting outcomes, and resuming durable handover state.
      Apache 2.0
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables comprehensive software lifecycle management with structured tracking of requirements, tasks, and architecture decisions through an SQLite database with full traceability and automated state validation.
      38
      MIT
    • F
      license
      Not graded
      quality
      D
      maintenance
      Transforms ideas into detailed, executable development plans with built-in verification, lessons learned tracking, and GitHub issue remediation workflows. Guides Claude through structured interviews, plan generation, execution with Haiku agents, and verification with Sonnet agents to maintain context and code quality across sessions.
      7
      -
    • A
      license
      Not graded
      quality
      F
      maintenance
      An autonomous software-engineering pipeline for Claude Code that runs on real evidence: codebase intelligence tools, git analytics, deterministic verification rules, and zero LLM-judges-LLM. Every claim traces to a paper and every PR passes its own gates.
      1
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Gives Claude Code sessions a durable, shared memory and work ledger backed by a local SQLite database, exposing the brain_* tools so agents can create and lock goals with verifiable success criteria, plan and track work units, record evidence and failures, and search decisions, learnings and project knowledge. Because the tool descriptions carry the operating rules, every session in every project reads and writes the same accumulating context instead of starting from scratch.
      MIT

    TDQS

    A4.1/5.0

    Scored across 7 tools

    Disambiguation5/5

    Each tool has a distinct job: start a run, advance a phase, check progress, list runs, and load skill metadata/content. The only close pair, forge_next and forge_status, is separated by guidance vs. state, so an agent should not misselect.

    Naming Consistency4/5

    All tools share the forge_ prefix and snake_case, making them predictable. However, the pattern mixes verbs (start, complete_phase) with bare nouns (status, tasks, skills, skill), so it is not a fully consistent verb_noun convention.

    Tool Count5/5

    Seven tools is well-scoped for a pipeline-orchestration server. Each tool covers a necessary part of the run lifecycle or skill access without redundancy or bloat.

    Completeness4/5

    The core lifecycle is covered: start, advance, inspect status, list runs, and load skills. The only notable gap is the lack of an explicit cancel/abort operation for a run, though that may be intentionally unsupported by the guided pipeline model.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues