Skip to main content
Glama
Ajey95

ImmunoGraph MCP

by Ajey95
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Related Servers

Alternatives to ImmunoGraph MCP

No user-submitted related servers found.

    Related Servers

    • provmcp

      AbhiAdhikari
      A
      license
      Not graded
      quality
      C
      maintenance
      Enables provenance capture and replay verification for scientific MCP tool calls, using a signed hash-chained ledger and data-source release resolution.
      MIT

    • GnosisLab

      cloudcell
      A
      license
      A
      quality
      A
      maintenance
      Enables AI agents and MCP clients to run research as an explicit scientific process: forming hypotheses, designing and executing sealed experiments, capturing observations and artifacts, linking claims to supporting evidence, and reviewing provenance. Exposes coordinated MCP services so users can inspect, reproduce, and audit every step from question to conclusion rather than trusting an opaque final answer.
      46
      223 PyPI
      21
      Apache 2.0

    • bourne mcp

      KozakHou
      A
      license
      A
      quality
      A
      maintenance
      Provides MCP access to plan and execute reproducible computational experiments with immutable execution plans, artifact provenance, verification checks, and support for direct, Slurm, and PBS backends.
      17
      Apache 2.0

    • SciAgentKit

      ehsansyh
      A
      license
      Not graded
      quality
      C
      maintenance
      MCP-native scientific skills for reproducible computational biology and AI-driven drug-discovery workflows. It combines deterministic scientific tools with an MCP server to give AI agents real computational capabilities.
      Apache 2.0
    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A4.1/5.0

    Scored across 46 tools

    Disambiguation4/5

    Despite 46 tools, descriptions consistently state scope boundaries and name explicit alternatives (predict_mhci vs predict_mhcii vs predict_bcell, compute_consensus vs compute_consensus_batch, remove_duplicate_candidates vs deduplicate_compounds, generate_report vs export_candidates). A few near-neighbors remain easy to confuse at a glance—the synthetic vs authoritative pairs, and create_molstar_view vs visualize_results vs generate_report—but the prose resolves them. No two tools appear to do the same thing.

    Naming Consistency5/5

    Every tool is snake_case with a verb-first, object-second pattern (validate_sequence, calculate_surface_accessibility, prepare_ligand, run_docking, export_workflow_trace). Suffix modifiers like _batch and prefixes like compute_/calculate_ are used consistently within their families. Minor quirks (predict_mhci without a separator before the numeral) do not break predictability.

    Tool Count3/5

    The 46 tools map onto genuinely distinct pipeline stages—sequence, prediction, consensus, constraints, structure, chemistry, docking, reporting, and orchestration—so most earn their place rather than being padding. Still, 46 is heavy for a single MCP surface and forces an agent to plan across many stages, with several parallel 'synthetic/demo' twins adding surface area.

    Completeness4/5

    The surface covers the full lifecycle from sequence validation through prediction, normalization, consensus, ranking, constraints, structure mapping, docking, interaction analysis, and reporting/orchestration export. Gaps are minor: no allele/population listing or lookup tools, no async job status or artifact retrieval, and no cleanup or cache management operations.

    Maintenance

    ActivityMaintained
    ResponsivenessUnresponsive

    Resources